├── .github ├── ISSUE_TEMPLATE │ ├── bug_report.md │ ├── content_maintenance.md │ ├── site_chore.md │ ├── site_feature.md │ └── topic_request.md ├── PULL_REQUEST_TEMPLATE │ ├── code_template.md │ └── content_template.md └── workflows │ └── autobuild.yml ├── .gitignore ├── .prettierrc.js ├── .vscode └── settings.json ├── .vuepress ├── components │ ├── Glossary.vue │ ├── LatestChanges.vue │ ├── PageDiff.vue │ ├── PagesInCategory.vue │ ├── PythonPanel.vue │ ├── TopicIndex.vue │ └── ZTopicIndex.vue ├── config.js ├── packages │ └── vuepress-plugin-minimal-analytics │ │ ├── LICENSE │ │ ├── README.md │ │ ├── index.js │ │ ├── inject.js │ │ └── package.json ├── public │ ├── CNAME │ ├── acronyms.csv │ ├── bikes.jpg │ ├── og-image.jpg │ ├── seattle.jpg │ ├── tfr-logo-title.png │ ├── tfr-logo-title.svg │ ├── tfr-logo-very-tiny.png │ ├── tfr-logo.png │ ├── tfr-logo.svg │ ├── tiny-logo.png │ └── topics │ │ ├── 20160503ITM_WiesPresentation.pdf │ │ ├── ABMDTAIntegrationAggregateFeedback.jpg │ │ ├── ABMDTAIntegrationDirect.jpg │ │ ├── Abm-cav5-model.png │ │ ├── Accessibilities1.png │ │ ├── Accessibilities2.png │ │ ├── Accessibilities4.png │ │ ├── Accessibilities5.png │ │ ├── AccessibilityMunich.png │ │ ├── ActivityPurposeLegend.png │ │ ├── Agg-choice-variance.png │ │ ├── Agg_choice_eq2.png │ │ ├── AgglomerationVsSpatialCompetion.jpg │ │ ├── Approach_ABM.jpg │ │ ├── Approach_ATB.jpg │ │ ├── Approach_Hybrid.jpg │ │ ├── Architcture_of_system.JPG │ │ ├── Autonomous_Vehicles_Charrette_Participants.jpeg │ │ ├── AutoregressionExampleDetails.jpg │ │ ├── Av_modeling_recipe.png │ │ ├── AveragingMethods.jpg │ │ ├── BPR_Function.jpg │ │ ├── BeachBypassBluetoothExample.jpg │ │ ├── Behavior.jpg │ │ ├── CAMPO_CAV_Modeling_Experiment_Table_1.jpg │ │ ├── CAV_Operation_1.png │ │ ├── CAV_Operation_1_s.png │ │ ├── CAV_Operation_2.png │ │ ├── CAV_Operation_2_s.png │ │ ├── CAV_Penetration_Rates_1.png │ │ ├── CAV_Penetration_Rates_2.png │ │ ├── CAV_Penetration_Rates_3.png │ │ ├── ChattanoogaDistrict2District.jpg │ │ ├── ChoiceHierarchy.jpg │ │ ├── Choicesetdepiction.png │ │ ├── CoefficientOfVariation.PNG │ │ ├── CoincidenceRatio.JPG │ │ ├── Completed_STOPS_UI.jpg │ │ ├── DChoiceMathFormdisttowork.jpg │ │ ├── DemandSupplyPlacement.jpg │ │ ├── DestChoice_MathFormulation_Fig-1.jpg │ │ ├── DestinationChoiceArrows.png │ │ ├── DestinationChoiceSizeTermData.png │ │ ├── Destination_Choice_Charrette_Participants.jpg │ │ ├── Dta-flowchart.png │ │ ├── ExampleModelRevision.png │ │ ├── ExpansionMethods.jpg │ │ ├── Explosionofchoicealternatives.png │ │ ├── FerryData.jpg │ │ ├── GIGO.jpeg │ │ ├── GdotFreightModel.png │ │ ├── GdotPersonTravelModel.gif │ │ ├── HighwayModeSegmentation.jpg │ │ ├── HighwayNetworkLinkExample.png │ │ ├── Impact_and_Implementation.png │ │ ├── ImpedanceFunction.png │ │ ├── IntegerizingTripTables.jpg │ │ ├── JDouglasCarroll.png │ │ ├── JTWscatterplot.jpg │ │ ├── LL.JPG │ │ ├── LUTdataFlow.jpg │ │ ├── LUTfeedbackCycle.GIF │ │ ├── LandUseModelCommonElements.jpg │ │ ├── Link_Characterstics.jpg │ │ ├── LocationDataExample.jpg │ │ ├── Logsum1.png │ │ ├── Logsum2.png │ │ ├── LutIntegration2.jpg │ │ ├── MAG_Highway_Networks.jpg │ │ ├── MAG_Population_in_TAZ.jpg │ │ ├── MDCEVchoicealternatives.png │ │ ├── MaximumDesirableDeviation.jpg │ │ ├── Mdcevbaselineutilityexpression.png │ │ ├── Mdcevbudgetconstraint.png │ │ ├── Mdcevjacobian.png │ │ ├── Mdcevkuhntuckerconditions.png │ │ ├── Mdcevlagrangianfunction.png │ │ ├── Mdcevprobabilityexpression.png │ │ ├── Mdcevutilityfunction.png │ │ ├── MilwaukeeMitchellWindow.jpg │ │ ├── MilwaukeeMitchellWindowVirtualODLinks.jpg │ │ ├── MstmFlowChart.png │ │ ├── MstmNationwideStudyArea.png │ │ ├── MstmStatewideStudyArea.png │ │ ├── MultipleOptima.jpg │ │ ├── NetworkElements.jpeg │ │ ├── NewIntegrationMethods.jpg │ │ ├── NooutsidegoodconfigurationsMDCEV.png │ │ ├── OD_Travel_Fig.jpg │ │ ├── OutsidegoodconfigurationsMDCEV.png │ │ ├── PathFinding01.jpeg │ │ ├── PathFinding02.jpg │ │ ├── PathFinding04.jpg │ │ ├── PathFinding05.jpg │ │ ├── PathFinding3.jpg │ │ ├── Pathfinding.png │ │ ├── Pricing_forms.jpg │ │ ├── Pricing_treatments.png │ │ ├── ProjectLevelInterpolation.jpg │ │ ├── ProjectLevelProcess.jpg │ │ ├── ProjectLevelToolSelectionMatrix.jpg │ │ ├── RhoSquared.JPG │ │ ├── SANDAG_C04Report.pdf │ │ ├── SLC.jpg │ │ ├── STOPS_User_Interface.jpg │ │ ├── STOPS_output.jpg │ │ ├── Screenlines.png │ │ ├── SkimTable.png │ │ ├── States-with-operational-models-c.jpg │ │ ├── Stm_utility_cost.jpg │ │ ├── Strategic-model.png │ │ ├── TDM1-1.png │ │ ├── TLFD.jpg │ │ ├── TemporalTrendData.png │ │ ├── TimeUsePattern.png │ │ ├── TimeofDayHBW.png │ │ ├── Timespaceprism.png │ │ ├── TrafficAssignment.png │ │ ├── TrafficForecastRequestFormPage1.jpg │ │ ├── TrafficForecastRequestFormPage2.jpg │ │ ├── TrafficLandDevelopment.jpg │ │ ├── TransitModeSegmentation.jpg │ │ ├── Trip-based-cav5-model.png │ │ ├── TripBasedStaticIntegration.jpg │ │ ├── TurningMovementRefinement1.jpg │ │ ├── TurningMovementRefinement2.jpg │ │ ├── UE_Condition.jpg │ │ ├── UtilityOutsideGoodMDCEV.png │ │ ├── VMTperCapitaSeattle.jpg │ │ ├── VandR-Eq3-2.jpg │ │ ├── VandR-Eq6-2.jpg │ │ ├── VandR-Eq7-2.jpg │ │ ├── VandR-Eq9-1-2-1.jpg │ │ ├── VandR-Eq9-1-2-2.jpg │ │ ├── VandR-Eq9-1-2-3.jpg │ │ ├── VandR-Eq9-1-5-1.jpg │ │ ├── VandR-Fig1-1.jpg │ │ ├── VandR-Fig10-1.jpg │ │ ├── VandR-Fig2-1.jpg │ │ ├── VandR-Fig2-2.jpg │ │ ├── VandR-Fig2-3.jpg │ │ ├── VandR-Fig2-4.jpg │ │ ├── VandR-Fig3-1.jpg │ │ ├── VandR-Fig3-2.jpg │ │ ├── VandR-Fig3-3.jpg │ │ ├── VandR-Fig4-1.jpg │ │ ├── VandR-Fig6-1.jpg │ │ ├── VandR-Fig6-2.jpg │ │ ├── VandR-Fig6-3.jpg │ │ ├── VandR-Fig6-4.jpg │ │ ├── VandR-Fig6-5.jpg │ │ ├── VandR-Fig6-5b.jpg │ │ ├── VandR-Fig7-1.jpg │ │ ├── VandR-Fig8-1.jpg │ │ ├── VandR-Fig9-1.jpg │ │ ├── VandR-Fig9-10.jpg │ │ ├── VandR-Fig9-2.jpg │ │ ├── VandR-Fig9-3a.jpg │ │ ├── VandR-Fig9-3b.jpg │ │ ├── VandR-Fig9-4.jpg │ │ ├── VandR-Fig9-5.jpg │ │ ├── VandR-Fig9-6.jpg │ │ ├── VandR-Fig9-7.jpg │ │ ├── VandR-Fig9-8.jpg │ │ ├── VandR-Fig9-9.jpg │ │ ├── VehicleHoldingsTransactionsFramework_deJongKitamura.gif │ │ ├── Vehicleevolutionframework.jpg │ │ ├── Vinebuildingexample1.jpg │ │ ├── Vinebuildingexample2.jpg │ │ ├── Willingess_pay.png │ │ ├── count_continuous-1.png │ │ ├── count_discrete-1.png │ │ ├── countmodels_continuous-1.png │ │ ├── countmodels_discrete-1.png │ │ ├── countmodels_outcomes.png │ │ ├── countmodels_poissondist-1.png │ │ ├── hhByCarOwnership.png │ │ ├── hhBySize.png │ │ ├── hhTable.png │ │ ├── hhTable_1.png │ │ ├── hhTable_2.png │ │ ├── hhTable_3.png │ │ ├── hhTable_4.png │ │ ├── hhTable_5.png │ │ └── regressionCarsPopulation.png ├── scripts │ ├── acronym-builder.js │ └── build.sh ├── sidebar.js ├── styles │ ├── index.styl │ └── palette.styl └── theme │ ├── LICENSE │ ├── components │ ├── AlgoliaSearchBox.vue │ ├── DropdownLink.vue │ ├── DropdownTransition.vue │ ├── GdprBanner.vue │ ├── Home.vue │ ├── NavLink.vue │ ├── NavLinks.vue │ ├── Navbar.vue │ ├── Page.vue │ ├── PageEdit.vue │ ├── PageNav.vue │ ├── Sidebar.vue │ ├── SidebarButton.vue │ ├── SidebarGroup.vue │ ├── SidebarLink.vue │ ├── SidebarLinks.vue │ └── Z.vue │ ├── global-components │ └── Badge.vue │ ├── index.js │ ├── layouts │ ├── 404.vue │ └── Layout.vue │ ├── noopModule.js │ ├── styles │ ├── arrow.styl │ ├── code.styl │ ├── config.styl │ ├── custom-blocks.styl │ ├── index.styl │ ├── mobile.styl │ ├── toc.styl │ └── wrapper.styl │ └── util │ └── index.js ├── README.md ├── changes.md ├── events └── README.md ├── import-from-mediawiki.py ├── index.md ├── package.json ├── surveymanual ├── Chapter_11.md ├── Chapter_2.md ├── Chapter_3.md ├── Getting_Started.md ├── History_of_travel_surveys.md ├── Introduction.md ├── README.md └── thumb-linkvols.jpg ├── topics ├── 00_Table_Contents.md ├── 1st_TRB_Conference_on_Innovations_in_Travel_Modeling.md ├── 2012_Household_Travel_Survey_Symposium_Conference_Summary_and_Final_Report.md ├── 2nd_TRB_Conference_on_Innovations_in_Travel_Modeling.md ├── 3rd_TRB_Conference_on_Innovations_in_Travel_Modeling.md ├── 6th_ITM_Conference_Denver_Colorado_2016.md ├── 7th_ITM_Conference_Atlanta_Georgia_2018.md ├── ALBATROSS.md ├── ARC_s_Experience_Using_its_CT_RAMP_Activity_Based_Model.md ├── A_historical_perspective_of_innovations_in_travel_modeling.md ├── About.md ├── Accessibility.md ├── Active_transport_modeling.md ├── Activity_Based_Modeling_Primer.md ├── Activity_Travel_Planning_and_Decision_Making_Behaviors.md ├── Activity_based_models.md ├── Air_quality_estimation_in_project_level_traffic_forecasting.md ├── Associations_Organizations_and_Committees.md ├── Autonomous_vehicles.md ├── Autonomous_vehicles_Behavioral_considerations.md ├── Autonomous_vehicles_CAV_Penetration_Rates.md ├── Autonomous_vehicles_Early_applications.md ├── Autonomous_vehicles_Forecasting.md ├── Autonomous_vehicles_Lexicon.md ├── Autonomous_vehicles_Modeling_frameworks.md ├── Autonomous_vehicles_operation_network.md ├── Autonomous_vehicles_planning_and_policy_context.md ├── Autonomous_vehicles_use_cases.md ├── Autoregressive_models_in_project_forecasting.md ├── Average_Annual_Daily_Traffic.md ├── Average_Daily_Traffic.md ├── Benefits_of_Activity_Based_Models.md ├── Benefits_of_dynamic_network_models.md ├── Big_Data.md ├── Big_Picture.md ├── Box_Cox_transformations_in_project_level_traffic_forecasting.md ├── Bypasses_in_project_level_traffic_forecasting.md ├── Cellular_Communications_Data.md ├── Choice_Model_Development_in_Practice.md ├── Choice_Models_with_Aggregate_Choices.md ├── Choice_models.md ├── Choice_of_techniques_in_project_level_traffic_forecasts.md ├── Choicesetdepiction.png ├── Commercial_vehicle_surveys.md ├── Community.md ├── Content_Charrette_Autonomous_Vehicles.md ├── Content_Charrette_Destination_Choice_Models.md ├── Contributing-Dev-Instructions.md ├── Contributing.md ├── Count_Models.md ├── Current_Status_of_Statewide_Models.md ├── Current_trends_in_travel_behavior.md ├── DRCOG_s_Experience_Using_its_FOCUS_Activity_Based_Model.md ├── DTA_Primer.md ├── Dallas_Case_Study.md ├── Data_Development.md ├── Data_Driven_Methods.md ├── Data_Visualization.md ├── Delay_Estimation_in_Trip_Based_Models.md ├── Design_Hourly_Volume.md ├── Design_principles_of_land_use_models.md ├── DestChoice_MathFormulation_Fig-1.jpg ├── Destination_Choice_Calibration_and_Validation.md ├── Destination_Choice_Data_Sources.md ├── Destination_Choice_Implementation_and_Application.md ├── Destination_Choice_Mathematical_Formulation.md ├── Destination_Choice_Models.md ├── Destination_Choice_Parameter_Estimation.md ├── Destination_Choice_Set_Formation.md ├── Destination_Choice_Theoretical_Foundations.md ├── Development_of_Guidelines_for_TxDOT_Regional_Toll_Authority_Cooperation_and_Coordination.md ├── Discussion_of_travel_delay_in_acceptable_models_in_project_level_traffic_forecasting.md ├── Documentation_standards_in_project_level_traffic_forecasting.md ├── Dynamic_Traffic_Assignment.md ├── Dynamic_network_models.md ├── Empirical_Accuracy_of_Travel_Forecasts.md ├── Equity_Analysis.md ├── Errors_and_variability_in_volume_data_for_project_level_traffic_forecasts.md ├── Establishment_surveys.md ├── Example_of_an_autoregression_model_with_Box_Cox_transformation.md ├── Explaining_Activity_Based_Models_to_a_General_Audience.md ├── External_surveys.md ├── Factors_Affecting_Destination_Choice.md ├── Format_Testing.md ├── Freight_assignment.md ├── Freight_modeling.md ├── Future_Development_of_TFR.md ├── Future_prospect_for_activity_based_models.md ├── GPS_Based_Pilot_Survey_of_Freight_Movements_in_the_Midwest_Region.md ├── GPS_enabled_surveys.md ├── Georgia_Statewide_Model.md ├── Getting_Started.md ├── Global_Positioning_Systems_GPS_Data.md ├── Goods_Movement_Study_in_Illinois_Application_to_Freight_Transportation_and_Logistics.md ├── Guidelines_for_Network_Representation_of_Transit_Access_State_of_the_Practice_Summary.md ├── H_GAC_Activity_Based_Model_Model_Validation_Plan_Report.md ├── Half_lane_rule_and_extensions_in_project_level_traffic_forecasting.md ├── Health_and_Transportation_Data.md ├── High_Occupancy_Toll_Lanes_Potential_for_Implementation_in_the_Atlanta_Region.md ├── Highway_Capacity_Manual.md ├── Highway_Research_Board_Special_Report_120_Urban_Commodity_Flow.md ├── Highway_networks.md ├── Highway_noise_analysis_in_project_level_traffic_forecasting.md ├── History_of_land_use_transport_modeling.md ├── Household_travel_surveys.md ├── Hybrid_models_in_project_level_traffic_forecasting.md ├── Ideal_travel_model_standard_in_project_level_traffic_forecasting.md ├── Impacts_of_Time_of_Day_Pricing_on_Travel_Behavior_General_Findings_from_the_Port_Authority_of_New_York_and_New_Jersey_s_Initiative.md ├── Impedance.md ├── Including_TRB_sponsored_research.md ├── Innovations_in_Travel_Modeling.md ├── Inside_the_Black_Box.md ├── Integrated_Travel_Demand_and_Network_Models.md ├── Interpolation_between_forecast_years_in_project_level_traffic_forecasting.md ├── Iterative_Proportional_Fitting.md ├── J_Douglas_Carroll.md ├── Joint_Conditional_Destination_Choices.md ├── Joint_Travel_Behavior.md ├── LM1.md ├── LM2.md ├── Land_use_models_in_project_level_traffic_forecasting.md ├── Land_use_transport_model_types.md ├── Land_use_transport_modeling.md ├── Limitations_in_classic_constraint_based_approaches.md ├── Limited_role_of_judgment_in_project_level_traffic_forecasting.md ├── Linear_models_with_explanatory_variables_in_project_level_traffic_forecasting.md ├── List_of_Model_User_Groups.md ├── Location_Based_Services_Data.md ├── Long_distance_Travel.md ├── Long_range_transportation_plan.md ├── MATSim.md ├── MPO_model_documentation.md ├── Market_Segmentation.md ├── Markov_Models.md ├── Maryland_Statewide_Transportation_Model.md ├── Measures_of_effectiveness_and_performance_measures_in_project_level_traffic_forecasting.md ├── Modal_hierarchy.md ├── Mode_Choice_Behavior.md ├── Mode_choice.md ├── Model_Data_Management.md ├── Model_Improvement_Plan.md ├── Model_Transferability.md ├── Model_Validation_and_Reasonableness_Checking.md ├── Model_Validation_and_Reasonableness_Checking_Amount_Of_Travel.md ├── Model_Validation_and_Reasonableness_Checking_Assignment.md ├── Model_Validation_and_Reasonableness_Checking_Distribution.md ├── Model_Validation_and_Reasonableness_Checking_Documentation.md ├── Model_Validation_and_Reasonableness_Checking_Figures.md ├── Model_Validation_and_Reasonableness_Checking_Introduction.md ├── Model_Validation_and_Reasonableness_Checking_Mode_Choice.md ├── Model_Validation_and_Reasonableness_Checking_Model_Inputs.md ├── Model_Validation_and_Reasonableness_Checking_Socioeconomic_Models.md ├── Model_Validation_and_Reasonableness_Checking_Tables.md ├── Model_Validation_and_Reasonableness_Checking_Temporal_And_Sensitivity.md ├── Model_Validation_and_Reasonableness_Checking_Time_Of_Day.md ├── Model_Validation_and_Reasonableness_Checking_Validation_Plan.md ├── Model_calibration.md ├── Model_calibration_and_validation.md ├── Model_estimation.md ├── Model_estimation_software.md ├── Model_integration.md ├── Model_validation_plans.md ├── Modelers.md ├── Modeling_Uncertainty.md ├── Multi_resolution_models.md ├── Multiple_Discrete_Continuous_Extreme_Value_MDCEV_Model.md ├── NCHRP_775_Applying_GPS_Data_to_Understand_Travel_Behavior.md ├── NCHRP_Report_765.md ├── NCHRP_Synthesis_406_Advanced_Practices_in_Travel_Forecasting_A_Synthesis_of_Highway_Practice.md ├── NCTCOG_Path_Towards_Advanced_Analytical_Tools.md ├── National_guidelines_for_use_in_project_level_traffic_forecasting.md ├── Network_assignment.md ├── New_Starts.md ├── OD_table_refinements_in_project_level_traffic_forecasting.md ├── On_Board_Transit_Survey.md ├── Online_Travel_Survey_Manual.md ├── Open_Code_Directory.md ├── Open_Data_Sources.md ├── Open_Matrix_Format.md ├── Ordered_Response_Models.md ├── Origin_Destination.md ├── Parking_surveys.md ├── Path_Choice_Mode_choice_Consistency.md ├── Path_Finding_Algorithm.md ├── Pavement_design_in_project_level_traffic_forecasting.md ├── Pivoting_with_select_link_analysis_for_small_developments_in_project_level_traffic_forecasting.md ├── Plausibility_Assessment_of_a_Travel_Forecast.md ├── Polaris.md ├── Policy_relevance_of_transportation_models.md ├── Population_Synthesis.md ├── Population_Synthesis_For_Microsimulating_Travel_Behavior.md ├── Prerequisites_for_travel_modeling.md ├── Pricing_and_Travel_Time_Reliability_Enhancements_in_the_SANDAG_Activity_Based_Travel_Model_Final_Report.md ├── Pricing_and_valuation.md ├── Project_level_forecasting_process.md ├── Project_level_traffic_forecasting.md ├── Public_transport_transit_modeling.md ├── Puget_Sound_Regional_Council.md ├── Purpose_of_project_level_travel_forecasting.md ├── Python_Test.md ├── Quality_assurance_and_validation_standards_in_project_level_traffic_forecasting.md ├── README.md ├── Refining_speeds_for_evaluation_in_project_level_traffic_forecasting.md ├── Refining_vehicle_class_forecasts_for_evaluation_in_project_level_traffic_forecasting.md ├── Regression_Analysis.md ├── Regulatory_framework_for_metropolitan_modeling.md ├── Reporting_of_reasonable_bounds_on_forecast_values_in_project_level_traffic_forecasting.md ├── Reports.md ├── Representations_of_Decision_Making_Behavior_in_Travel_Modeling.md ├── Resources.md ├── Response_bias.md ├── SFCTA_Paper_incorporating_crowding.md ├── SFCTA_s_Experience_Using_its_SF_CHAMP_Activity_Based_Model.md ├── SHRP2_C04_Improving_Our_Understanding_of_How_Highway_Congestion_and_Pricing_Affect_Travel_Demand.md ├── SR_288_Metropolitan_Travel_Forecasting_Current_Practice_and_Future_Direction.md ├── STOPS.md ├── Safety_Analysis.md ├── Safety_Data.md ├── Scenario_Forecasting_for_Travel_Demand_Modeling.md ├── Scenario_sensitivity_testing_in_project_level_traffic_forecasting.md ├── Screenline_refinements_in_project_level_traffic_forecasting.md ├── Sketch_planning_models.md ├── Skim_Matrix.md ├── Smoothing_in_project_level_traffic_forecasting.md ├── Software.md ├── Software_Development_For_Travel_Modeling.md ├── Solution_Algorithm.md ├── Spatial_data.md ├── Spatial_interaction_models.md ├── Special_reporting_requirements_in_project_level_traffic_forecasting.md ├── Speed_and_travel_time_refinements_in_project_level_traffic_forecasting.md ├── Stated_preference_surveys.md ├── Statewide_Freight_Modeling.md ├── Statewide_Modeling_Case_Studies.md ├── Statewide_Modeling_Subcommittee_ADA10_2_.md ├── Statewide_Models_Activity_based_Models.md ├── Statewide_Models_ODME_Models.md ├── Statewide_Models_Special_Models.md ├── Statewide_Models_Trip_based_Models.md ├── Statewide_models.md ├── Statewide_peer_exchange.md ├── Stepwise_Model_Calibration_Validation.md ├── Stochastic_Traffic_Assignment.md ├── Strategic_Models.md ├── Style_Guide.md ├── Subarea_focusing_in_project_level_traffic_forecasting.md ├── Synthetic_populations_review_of_the_different_approaches.md ├── TCRP_Report_95_Chapter_12_Transit_Pricing_and_Fares_Traveler_Response_to_Transportation_System_Changes.md ├── TCRP_Report_95_Chapter_13_Parking_Pricing_and_Fares_Traveler_Response_to_Transportation_System_Changes.md ├── TCRP_Report_95_Chapter_14_Road_Value_Pricing_Traveler_Response_to_Transportation_System_Changes.md ├── TCRP_Synthesis_63.md ├── TMIP.md ├── TMIP_Activity_Based_Model_Webinar_Series_Instructor_Manual.md ├── TRANSIMS.md ├── T_PICS_Transportation_Project_Impact_Case_Studies.md ├── Temporal_data.md ├── Temporal_refinements_and_directional_split_refinements_in_project_level_traffic_forecasting.md ├── Temporal_resolution_in_project_level_traffic_forecasting.md ├── The_ARC_and_SACOG_Experience_with_Activity_Based_Models_Synthesis_and_Lessons_Learned.md ├── The_Chicago_Area_Transportation_Study_Creating_the_First_Plan_1955_1962_.md ├── The_Transportation_Planning_Process_Key_Issues.md ├── Time_of_Day_Factoring.md ├── Tolling_and_Public_Private_Partnerships_in_Texas_Separating_Myth_from_Fact.md ├── Topic_Circles.md ├── Tour_based_and_supply_chain_modeling_for_freight.md ├── Tour_based_models.md ├── Toward_a_dynamic_model_of_individual_activity_pattern_formulation.md ├── Traffic_Analysis_Zone.md ├── Traffic_Data.md ├── Traffic_dynamics_in_project_level_traffic_forecasting.md ├── Traffic_microsimulation_in_project_level_traffic_forecasting.md ├── Traffic_simulation_models.md ├── Transit_Data.md ├── Transit_Fares.md ├── Transit_Network_Assignment.md ├── Transit_Network_Service_Determination.md ├── Transit_Path_Parameters.md ├── Transit_Route.md ├── Transit_Route_Frequency.md ├── Transit_Vehicles.md ├── Transit_crowding.md ├── Transit_dwell_time.md ├── Transit_mode_combinations.md ├── Transit_networks.md ├── Transit_onboard_surveys.md ├── Transportation_Elasticities_How_Prices_and_Other_Factors_Affect_Travel_Behavior.md ├── Transportation_networks.md ├── Transportation_secure_data_center.md ├── Travel_Behavior_Resources.md ├── Travel_Behavior_of_Diverse_Populations.md ├── Travel_Behaviour_A_review_of_recent_literature.md ├── Travel_Demand_and_Network_Model_Integration_Schemas.md ├── Travel_Forecasting_Results_Report.md ├── Travel_Forecasting_for_the_Capital_Investment_Grant_Program.md ├── Travel_Time_Speed_and_Reliability_Data.md ├── Travel_behavior.md ├── Travel_model_curriculum.md ├── Travel_survey_data.md ├── Travel_surveys.md ├── Trend_models_in_project_level_traffic_forecasting.md ├── Trip_Generation.md ├── Trip_based_models.md ├── Trip_distribution.md ├── Trip_interchange.md ├── Turning_movement_refinements_in_project_level_traffic_forecasting.md ├── Twin_Cities_HOV_Study_Final_Report.md ├── Two_Lane_Highways.md ├── UrbanDataResources.md ├── Urban_Big_Data.md ├── Urban_Data.md ├── Urban_and_metropolitan_models.md ├── User_Equilibrium.md ├── User_benefits_in_project_level_traffic_forecasting.md ├── Using_policy_to_affect_travel_behavior.md ├── Utility.md ├── Validating_Input_Data.md ├── Vehicle_Counts.md ├── Vehicle_Ownership_Models.md ├── Vehicle_mix_refinements_in_project_level_traffic_forecasting.md ├── Version_Control.md ├── Vine_building.md ├── Visitor_surveys.md ├── Washington_State_Comprehensive_Tolling_Study_Volume_1_Final_Report.md ├── Webinars_and_Videos.md ├── Windowing_with_OD_table_estimation_from_traffic_counts_in_project_level_traffic_forecasting.md ├── Working_with_vehicle_re_identification_data_in_project_level_traffic_forecasting.md └── glossary.md ├── vscode-tfresource.code-workspace └── yarn.lock /.github/ISSUE_TEMPLATE/bug_report.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: 🐞 Bug report 3 | about: Report a bug in site build or deploy process 4 | title: '🐞 Bug: ' 5 | labels: 'bug' 6 | assignees: '@billyc' 7 | --- 8 | 9 | ## Current Behavior 10 | 11 | 12 | ## Desired Behavior 13 | 14 | 15 | ## 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/.vuepress/packages/vuepress-plugin-minimal-analytics/package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "vuepress-plugin-minimal-analytics", 3 | "version": "0.1.4", 4 | "description": "Minimal Google Analytics plugin for VuePress", 5 | "main": "index.js", 6 | "scripts": { 7 | "version": "git add --all", 8 | "postversion": "git push && git push --tags" 9 | }, 10 | "repository": { 11 | "type": "git", 12 | "url": "git+https://github.com/webmasterish/vuepress-plugin-minimal-analytics.git" 13 | }, 14 | "keywords": [ 15 | "vue", 16 | "vuepress", 17 | "plugin", 18 | "vuepress-plugin", 19 | "analytics", 20 | "google-analytics" 21 | ], 22 | "author": { 23 | "name": "webmasterish", 24 | "email": "webmasterish@gmail.com", 25 | "url": "https://webmasterish.com" 26 | }, 27 | "license": "MIT", 28 | "homepage": "https://github.com/webmasterish/vuepress-plugin-minimal-analytics", 29 | "bugs": { 30 | "url": "https://github.com/webmasterish/vuepress-plugin-minimal-analytics/issues" 31 | }, 32 | "engines": { 33 | "node": ">=8" 34 | }, 35 | "files": [ 36 | "index.js", 37 | "inject.js", 38 | "README.md", 39 | "LICENSE" 40 | ] 41 | } 42 | -------------------------------------------------------------------------------- /.vuepress/public/CNAME: -------------------------------------------------------------------------------- 1 | tfresource.org 2 | -------------------------------------------------------------------------------- /.vuepress/public/acronyms.csv: -------------------------------------------------------------------------------- 1 | ACRONYM, DEFINITION, OPTIONAL-LINK 2 | TAZ, Traffic Analysis Zone, /topics/Traffic_Analysis_Zone 3 | TFR, Travel Forecasting Resource, /topics/Big_Picture 4 | TRB, Transportation Research Board, https://www.trb.org 5 | ABM, Activity-Based Models, /topics/Activity_based_models 6 | FAF, Freight Analysis Framework, https://faf.ornl.gov/faf5/ 7 | PCE, Passenger 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../.vuepress/public/latest-changes.csv 8 | cd .. 9 | 10 | node .vuepress/scripts/acronym-builder.js 11 | yarn install 12 | yarn build 13 | 14 | -------------------------------------------------------------------------------- /.vuepress/styles/palette.styl: -------------------------------------------------------------------------------- 1 | // defaults 2 | $textColor = #181825 3 | $sideBlue = #eaeaea 4 | $pageColor = #f8f8f8 5 | $mediumZoomZIndex = 10000 6 | $accentColor = #393 7 | $contentWidth = 700px 8 | $codeBgColor = #455 9 | $navbarHeight = 3.1rem 10 | $arrowBgColor = #4a4 11 | $navbar-bg = #258 12 | $sideSection = #277 13 | $acronymPopup = #369 -------------------------------------------------------------------------------- /.vuepress/theme/LICENSE: -------------------------------------------------------------------------------- 1 | The MIT License (MIT) 2 | 3 | Copyright (c) 2018-present, Yuxi (Evan) You 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in 13 | all copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN 21 | THE SOFTWARE. 22 | -------------------------------------------------------------------------------- /.vuepress/theme/components/DropdownTransition.vue: -------------------------------------------------------------------------------- 1 | 11 | 12 | 28 | 29 | 34 | -------------------------------------------------------------------------------- /.vuepress/theme/components/NavLink.vue: -------------------------------------------------------------------------------- 1 | 21 | 22 | 55 | -------------------------------------------------------------------------------- /.vuepress/theme/components/Sidebar.vue: -------------------------------------------------------------------------------- 1 | 9 | 10 | 22 | 23 | 60 | -------------------------------------------------------------------------------- /.vuepress/theme/components/SidebarButton.vue: -------------------------------------------------------------------------------- 1 | 8 | 9 | 29 | -------------------------------------------------------------------------------- /.vuepress/theme/global-components/Badge.vue: -------------------------------------------------------------------------------- 1 | 25 | 26 | 45 | -------------------------------------------------------------------------------- /.vuepress/theme/index.js: -------------------------------------------------------------------------------- 1 | const path = require('path') 2 | 3 | // Theme API. 4 | module.exports = (options, ctx) => { 5 | const { themeConfig, siteConfig } = ctx 6 | 7 | // resolve algolia 8 | const isAlgoliaSearch = ( 9 | themeConfig.algolia 10 | || Object 11 | .keys(siteConfig.locales && themeConfig.locales || {}) 12 | .some(base => themeConfig.locales[base].algolia) 13 | ) 14 | 15 | const enableSmoothScroll = themeConfig.smoothScroll === true 16 | 17 | return { 18 | alias () { 19 | return { 20 | '@AlgoliaSearchBox': isAlgoliaSearch 21 | ? path.resolve(__dirname, 'components/AlgoliaSearchBox.vue') 22 | : path.resolve(__dirname, 'noopModule.js') 23 | } 24 | }, 25 | 26 | plugins: [ 27 | ['@vuepress/active-header-links', options.activeHeaderLinks], 28 | '@vuepress/search', 29 | '@vuepress/plugin-nprogress', 30 | ['container', { 31 | type: 'tip', 32 | defaultTitle: { 33 | '/': 'TIP', 34 | '/zh/': '提示' 35 | } 36 | }], 37 | ['container', { 38 | type: 'warning', 39 | defaultTitle: { 40 | '/': 'WARNING', 41 | '/zh/': '注意' 42 | } 43 | }], 44 | ['container', { 45 | type: 'danger', 46 | defaultTitle: { 47 | '/': 'WARNING', 48 | '/zh/': '警告' 49 | } 50 | }], 51 | ['smooth-scroll', enableSmoothScroll] 52 | ] 53 | } 54 | } 55 | -------------------------------------------------------------------------------- /.vuepress/theme/layouts/404.vue: -------------------------------------------------------------------------------- 1 | 10 | 11 | 27 | -------------------------------------------------------------------------------- /.vuepress/theme/noopModule.js: -------------------------------------------------------------------------------- 1 | export default {} 2 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/arrow.styl: -------------------------------------------------------------------------------- 1 | @require './config' 2 | 3 | .arrow 4 | display inline-block 5 | width 0 6 | height 0 7 | &.up 8 | border-left 4px solid transparent 9 | border-right 4px solid transparent 10 | border-bottom 6px solid $arrowBgColor 11 | &.down 12 | border-left 4px solid transparent 13 | border-right 4px solid transparent 14 | border-top 6px solid $arrowBgColor 15 | &.right 16 | border-top 4px solid transparent 17 | border-bottom 4px solid transparent 18 | border-left 6px solid $arrowBgColor 19 | &.left 20 | border-top 4px solid transparent 21 | border-bottom 4px solid transparent 22 | border-right 6px solid $arrowBgColor 23 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/config.styl: -------------------------------------------------------------------------------- 1 | $contentClass = '.theme-default-content' 2 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/custom-blocks.styl: -------------------------------------------------------------------------------- 1 | .custom-block 2 | .custom-block-title 3 | font-weight 600 4 | margin-bottom -0.4rem 5 | &.tip, &.warning, &.danger 6 | padding .1rem 1.5rem 7 | border-left-width .5rem 8 | border-left-style solid 9 | margin 1rem 0 10 | &.tip 11 | background-color #f3f5f7 12 | border-color #42b983 13 | &.warning 14 | background-color rgba(255,229,100,.3) 15 | border-color darken(#ffe564, 35%) 16 | color darken(#ffe564, 70%) 17 | .custom-block-title 18 | color darken(#ffe564, 50%) 19 | a 20 | color $textColor 21 | &.danger 22 | background-color #ffe6e6 23 | border-color darken(red, 20%) 24 | color darken(red, 70%) 25 | .custom-block-title 26 | color darken(red, 40%) 27 | a 28 | color $textColor 29 | 30 | 31 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/mobile.styl: -------------------------------------------------------------------------------- 1 | @require './config' 2 | 3 | $mobileSidebarWidth = $sidebarWidth * 0.82 4 | 5 | // narrow desktop / iPad 6 | @media (max-width: $MQNarrow) 7 | .sidebar 8 | font-size 15px 9 | width $mobileSidebarWidth 10 | .page 11 | padding-left $mobileSidebarWidth 12 | 13 | // wide mobile 14 | @media (max-width: $MQMobile) 15 | .sidebar 16 | top 0 17 | padding-top $navbarHeight 18 | transform translateX(-100%) 19 | transition transform .2s ease 20 | .page 21 | padding-left 0 22 | .theme-container 23 | &.sidebar-open 24 | .sidebar 25 | transform translateX(0) 26 | &.no-navbar 27 | .sidebar 28 | padding-top: 0 29 | 30 | // narrow mobile 31 | @media (max-width: $MQMobileNarrow) 32 | h1 33 | font-size 1.9rem 34 | {$contentClass} 35 | div[class*="language-"] 36 | margin 0.85rem -1.5rem 37 | border-radius 0 38 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/toc.styl: -------------------------------------------------------------------------------- 1 | .table-of-contents 2 | .badge 3 | vertical-align middle 4 | -------------------------------------------------------------------------------- /.vuepress/theme/styles/wrapper.styl: -------------------------------------------------------------------------------- 1 | $wrapper 2 | max-width $contentWidth 3 | margin 0 0 4 | padding 2rem 2.5rem 5 | @media (max-width: $MQNarrow) 6 | padding 2rem 7 | @media (max-width: $MQMobileNarrow) 8 | padding 1.5rem 9 | 10 | -------------------------------------------------------------------------------- /changes.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Recent Changes' 3 | categories: 4 | no_index: true 5 | editLink: false 6 | --- 7 | 8 | Topic pages in order of most recent changes. 9 | 10 | ## Pages 11 | 12 | 13 | -------------------------------------------------------------------------------- /events/README.md: -------------------------------------------------------------------------------- 1 | --- 2 | home: true 3 | heroImage: /seattle.jpg 4 | heroText: 'Innovations in Travel Modeling 2020' 5 | tagline: 'Join us in Seattle, Washington.' 6 | actionText: Register Now → 7 | actionLink: "http://itmconference.com/" 8 | footer: 'Copyright © 2016-present National Academy of Sciences and by the contributing authors. All rights reserved.' 9 | --- 10 | 11 | 12 | 13 | The 8th edition of the biannual conference where we get to focus for four days on advanced modeling techniques and the latest developments in modeling and forecasting. 14 | 15 | **Call for papers, schedule, deadlines, and more are all coming soon.** 16 | 17 | 18 | -------------------------------------------------------------------------------- /index.md: -------------------------------------------------------------------------------- 1 | --- 2 | home: true 3 | heroImage: /bikes.jpg 4 | heroText: 'Travel Forecasting, Explained' 5 | tagline: 'A collection of best practices for travel demand forecasting and travel survey methods.' 6 | footer: 'Copyright © 2020 National Academy of Sciences' 7 | features: 8 | - title: State of the practice 9 | details: 'This site collects the latest and most practical methods and tools available for travel modelers.' 10 | - title: Vetted 11 | details: 'More than a wiki: many pages are written and reviewed by leaders in our industry, including members of the TRB ADB45 committee.' 12 | - title: Help out! 13 | details: 'We welcome content from the entire travel forecasting community. Please help us keep the content fresh!' 14 | --- 15 | 16 | # What is the Travel Forecasting Resource ? 17 | 18 | This project came about due to a TRB research project designed to examine the state-of-the-practice in metropolitan travel forecasting. 19 | 20 | In the final report, [Metropolitan Travel Forecasting: Current Practice and Future Direction](/topics/SR_288_Metropolitan_Travel_Forecasting_Current_Practice_and_Future_Direction), the committee identified many recommendations to improve travel demand forecasting, including a national travel forecasting handbook to be developed and kept current. 21 | 22 | This suggestion was taken up by the forecasting community, and this TFResource is that handbook! We hope you find it useful. 23 | 24 | ## The next steps 25 | 26 | As of Fall 2024, the Transportation Research Board has discontinued the subcommittee that oversees the development of TF Resource. As a result, active development of this site has stopped. We are grateful for the long-standing contributions of many contributors, and look forward to determining the best way to move forward as a community with or beyond TF Resource. -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "tf-resource", 3 | "version": "2.0.0", 4 | "description": "Travel Forecasting Resource Website", 5 | "main": "index.js", 6 | "scripts": { 7 | "serve": "vuepress dev", 8 | "build": "vuepress build", 9 | "deploy": "vuepress build && surge -d https://tfresource.surge.sh .vuepress/dist" 10 | }, 11 | "repository": { 12 | "type": "git", 13 | "url": "git+https://github.com/billyc/tfresource.git" 14 | }, 15 | "keywords": [ 16 | "vuepress", 17 | "trb", 18 | "website" 19 | ], 20 | "author": "Billy Charlton", 21 | "license": "ISC", 22 | "bugs": { 23 | "url": "https://github.com/billyc/tfresource/issues" 24 | }, 25 | "homepage": "https://github.com/billyc/tfresource#readme", 26 | "devDependencies": { 27 | "pug": "^3.0.1", 28 | "pug-plain-loader": "^1.0.0", 29 | "vuepress": "^1.9.7" 30 | }, 31 | "dependencies": { 32 | "html-hint": "^0.2.4", 33 | "markdown-it": "^12.3.2", 34 | "markdown-it-footnote": "^3.0.2", 35 | "markdown-it-sub": "^1.0.0", 36 | "node-forge": "^1.3.1", 37 | "vue-cookies": "^1.7.4", 38 | "vuepress-plugin-git-log": "^1.0.1", 39 | "vuepress-plugin-mathjax": "^1.2.8", 40 | "vuepress-plugin-medium-zoom": "^1.1.5", 41 | "vuepress-plugin-minimal-analytics": "./.vuepress/packages/vuepress-plugin-minimal-analytics", 42 | "vuepress-plugin-smooth-scroll": "^0.0.7", 43 | "yarn": "^1.22.19" 44 | } 45 | } 46 | -------------------------------------------------------------------------------- /surveymanual/Chapter_2.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'The Generic Travel Survey Process' 3 | categories: 4 | - Survey Manual 5 | --- 6 | 7 | Note: Significant components of this chapter come from Chapter 2 of the FHWA Travel Survey Manual. Material has been reviewed and updated by Lisa Aultmann-Hall and Peter Stopher. 8 | 9 | ### 2.1 The Survey Implementation Process 10 | Most travel surveys (and other types of surveys, as well) follow a common implementation procedure. Backstrom and Hursh-Cesar (1981) divide the generic survey implementation process into the 20 steps listed in Table 2.1. These 20 steps can be classified into the five general stages shown in Figure 2.1: 11 | 12 | - Survey planning, 13 | 14 | - Survey design, 15 | 16 | - Field implementation, 17 | 18 | - Data preparation, and 19 | 20 | - Data analysis. 21 | 22 | This manual concentrates on the three middle stages: survey design, field implementation, and data preparation. The survey planning and data analysis stages are related to decisions about the scope and intended uses of the data including models and other analyses. For this manual, it is assumed that the agency has either developed a detailed vision for creation or revision of an existing modeling system or has identified a particular set of policy needs for which survey data is needed. 23 | 24 | Figure 2.1 shows the many functional relationships between the steps in the implementation of a generic travel survey. Decisions made at each point of the process affect many other elements of the survey effort. Once the need for a new travel survey has been identified, an agency needs to proceed with three tasks: compiling useful background information for the survey effort, designing the overall survey effort based on the recognized data needs and available data sources, and organizing the survey team and resources. 25 | -------------------------------------------------------------------------------- /surveymanual/Chapter_3.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Chapter 3 3 | categories: 4 | - Survey Manual 5 | --- 6 | 7 | ## This is my header 8 | This is my text. 9 | -------------------------------------------------------------------------------- /surveymanual/History_of_travel_surveys.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Our very short history of travel surveys' 3 | categories: 4 | - Survey Manual 5 | --- 6 | 7 | # History of Travel Surveys 8 | 9 | ...and someone will talk about the 20th century here. 10 | -------------------------------------------------------------------------------- /surveymanual/Introduction.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Introduction' 3 | categories: 4 | - Survey Manual 5 | --- 6 | 7 | ## Introduction 8 | 9 | Travel surveying has been around as long as there has been travel. 10 | -------------------------------------------------------------------------------- /surveymanual/README.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Survey Methods Manual' 3 | categories: 4 | no_index: true 5 | editLink: false 6 | --- 7 | 8 | This will be the new home of the Travel Survey Manual. These pages will be divided into sections below. 9 | 10 | Browse the available pages, or use the search box above to find something specific. 11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /surveymanual/thumb-linkvols.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tfresource/tfresource-website/3bc6a3eec31aeec4699d196a6c5b4c05e358dd6b/surveymanual/thumb-linkvols.jpg -------------------------------------------------------------------------------- /topics/3rd_TRB_Conference_on_Innovations_in_Travel_Modeling.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "3rd TRB Conference on Innovations in Travel Modeling" 3 | categories: 4 | - Innovations In Travel Modeling 5 | --- 6 | 7 | The 3rd TRB Conference on Innovations in Travel Modeling (ITM2010) was held at the Tempe Mission Palms Hotel and Conference Center at Arizona State University in Tempe, Arizona during May 10-12, 2010. The conference was attended by more than 200 academics and practitioners from the public and private sector enterprises. The conference included a mix of workshops, parallel sessions, plenary sessions, and interactive discussion sessions. A variety of networking events were also held as part of the conference. 8 | 9 | For complete information about the conference, including papers and presentations, please visit the [ITM2010 Website](http://itm2010.weebly.com). 10 | 11 | The Innovations in Travel Modeling (ITM) Conference Series was started in 2006 with a view to facilitate exchange of information between researchers and practitioners that would aid in moving new and advanced travel modeling methods into practice. The conference series has served a critical role in helping bring the research and practitioner communities together. Conferences are held every even year (alternating with the Transportation Planning Applications Conference Series). 12 | -------------------------------------------------------------------------------- /topics/A_historical_perspective_of_innovations_in_travel_modeling.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'A historical perspective of innovations in travel modeling' 3 | noTOC: true 4 | categories: 5 | - Innovations In Travel Modeling 6 | - Presentations 7 | - Resources 8 | - Travel Behavior 9 | links: 10 | - type: Presentation 11 | label: 'A historical perspective of innovations in travel modeling' 12 | url: 20160503ITM_WiesPresentation.pdf 13 | --- 14 | 15 | _A historical perspective of innovations in travel modeling_ 16 | 17 | #### Author 18 | 19 | Kermit Wies 20 | 21 | #### Source 22 | 23 | #### Abstract 24 | 25 | Originally delivered orally at the Tuesday Plenary, 2016 Innovations in Travel Modeling, Denver, Colorado 26 | 27 | #### Copyright & Usage Permissions 28 | 29 | #### Publication Date 30 | 31 | 2016-05-03 32 | -------------------------------------------------------------------------------- /topics/Activity_Based_Modeling_Primer.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Activity Based Modeling Primer" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models 6 | - Reports 7 | - Resources 8 | links: 9 | - type: Report (PDF) 10 | label: "Full Document" 11 | url: http://onlinepubs.trb.org/onlinepubs/shrp2/SHRP2_C46.pdf 12 | --- 13 | 14 | 15 | #### Author 16 | 17 | Joe Castiglione, Mark Bradley, and John Gliebe 18 | 19 | #### Source 20 | 21 | [SHRP2 C46](http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=3432) 22 | 23 | #### Abstract 24 | 25 | #### Copyright & Usage Permissions 26 | 27 | Copyright 2015 National Academy of Sciences. 28 | 29 | #### Publication Date 30 | 31 | Draft: 2014-Jun-30 32 | Final: 2015 33 | 34 | 35 | 36 | 37 | -------------------------------------------------------------------------------- /topics/Air_quality_estimation_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Air quality estimation in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Some states and locales are in attainment of the national ambient air quality standards (NAAQS) from the Clean Air Act, so there is little need for air quality analysis for highway projects. 8 | 9 | Otherwise, for guidance on estimating GHG emissions from HPMS data or from travel models, see FHWA’s, “Handbook for Estimating Transportation Greenhouse Gas Emissions for Integration into the Planning Process”. The methods presented in this Handbook are largely based on obtaining good VMT and speed estimates for a whole region. Emission factors may be improved by introducing a customized vehicle mix in MOVES. Although written for GHG gases, the advice in this Handbook applies equally well to the process of estimating energy consumption from highway vehicles. 10 | 11 | Considerable advice on this subject may also be found in the report from NCHRP Project 25-25/Task 96, “Quick Reference Guide For Transportation Planners/Engineers: Generating Traffic & Activity Data for Project-Level Air Quality:Analyses”. 12 | 13 | References 14 | ---------- 15 | 16 | FHWA, “Handbook for Estimating Transportation Greenhouse Gas Emissions for Integration into the Planning Process” 17 | 18 | “Quick Reference Guide For Transportation Planners/Engineers: Generating Traffic & Activity Data for Project-Level Air Quality:Analyses” Prepared for AASHTO Committee on Environment and Sustainability. WSP USA, Inc. and Cambridge Systematics, Inc. July 2018. See http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP25-25(96)_QRG.pdf 19 | 20 | -------------------------------------------------------------------------------- /topics/Average_Annual_Daily_Traffic.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Average Annual Daily Traffic" 3 | categories: 4 | - Transportation Networks 5 | --- 6 | 7 | According to [NCHRP Report 765](NCHRP_Report_765), average annual daily traffic (AADT) is the estimate of typical daily traffic on a road segment for all days of the week, Sunday through Saturday, over the period of 1 year. A true AADT is developed by utilizing a full year of traffic count data, such as data generated from a permanent traffic counter; however, for the purposes of the guidelines presented herein, the term AADT is used to show a factored ADT. The AADT adjustment factors include daily factors, weekly factors, seasonal adjustment factors, and axle correction factors developed from automatic traffic recorders (ATRs) that collect data continuously throughout the year. The AADT is the best measure of the total use of a road because it includes all traffic for an entire year. 8 | 9 | **It is important to always use AADT for traffic forecasting since a simple ADT may not be representative of the average traffic at the site being measured.** 10 | 11 | The formula for calculating AADT is: AADT = [ADT](Average_Daily_Traffic) * Adjustment Factor 12 | -------------------------------------------------------------------------------- /topics/Average_Daily_Traffic.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Average Daily Traffic" 3 | categories: 4 | - Transportation Networks 5 | --- 6 | 7 | According to [NCHRP Report 765](NCHRP_Report_765), average daily traffic (ADT) reflects the average number of vehicles that travel through a segment of roadway over a short-term period. The ADT is the raw, non-factored count data obtained by a short-term traffic count (usually a 24- to 48-hour period) typically collected on Tuesday, Wednesday, and Thursday. The ADT is an important, basic unit of traffic monitoring and is essential for developing traffic forecasts. 8 | -------------------------------------------------------------------------------- /topics/Choice_of_techniques_in_project_level_traffic_forecasts.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Choice of techniques in project-level traffic forecasts" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | There are a variety of techniques that might apply to any forecast. In addition, techniques may be used in combination to create a forecast. 11 | The “tools selection matrix” from [NCHRP Report 765](NCHRP_Report_765) may be used to help identify techniques that have merit for a particular project-level forecast. The figure below is a “tools selection matrix” customized for Hawaii. The “tools selection matrix” is used to both positively and negatively influence the choice of technique. 12 | 13 | See [NCHRP Report 765](NCHRP_Report_765) Appendix A for an illustrative example of how to use this matrix. The matrix identifies candidate techniques though this step-by-step process. 14 | 15 | 1. Identify all columns that correspond to the characteristics of the project and the forecast. 16 | 2. Shade each cell, containing an “X”, in an identified column. 17 | 3. Tentatively select techniques (rows) that are likely candidates by virtue of the number of shaded cells in their rows. 18 | 4. For each tentatively selected technique (row), identify contradictions. A contradiction is a cell with an “X” that is not shaded and is deemed critical to the technique. 19 | 5. Eliminate any technique (row) with a contradiction. 20 | 6. Review each remaining techniques for applicability to the project forecast. 21 | 22 | ![](ProjectLevelToolSelectionMatrix.jpg "ProjectLevelToolSelectionMatrix.jpg") 23 | 24 | -------------------------------------------------------------------------------- /topics/Choicesetdepiction.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tfresource/tfresource-website/3bc6a3eec31aeec4699d196a6c5b4c05e358dd6b/topics/Choicesetdepiction.png -------------------------------------------------------------------------------- /topics/Content_Charrette_Autonomous_Vehicles.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Content Charrette: Autonomous Vehicles" 3 | categories: 4 | - Autonomous Vehicles 5 | --- 6 | 7 | 8 | 9 | On November 7-8, 2017 the following individuals gathered for the express purpose of generating extensive content on the topic of Autonomous vehicles: 10 | 11 | ![Autonomous Vehicles Content Charrette Participants, November 2017](Autonomous_Vehicles_Charrette_Participants.jpeg "Autonomous Vehicles Content Charrette Participants, November 2017") 12 | 13 | - Rick Donnelly 14 | - Julie Dunbar 15 | - Greg Macfarlane 16 | - Brice Nichols 17 | - Dave Ory 18 | - Maren Outwater 19 | - Joan Walker 20 | 21 | The following pages were generated during this two day workshop: 22 | 23 | - [Planning and policy context](Autonomous_vehicles_planning_and_policy_context) 24 | - [Behavioral considerations](Autonomous_vehicles_Behavioral_considerations) 25 | - [Modeling frameworks](Autonomous_vehicles_Modeling_frameworks) 26 | - [Forecasting](Autonomous_vehicles_Forecasting) 27 | - [Use cases](Autonomous_vehicles_use_cases) 28 | - [Early applications](Autonomous_vehicles_Early_applications) 29 | 30 | 31 | -------------------------------------------------------------------------------- /topics/Content_Charrette_Destination_Choice_Models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Content Charrette: Destination Choice Models" 3 | categories: 4 | - Destination Choice Models 5 | --- 6 | 7 | On May 24-25, 2017 the following individuals gathered for the express purpose of generating extensive content on the topic of Destination Choice Models: 8 | 9 | ![Destination Choice Content Charrette Participants, May 2017](Destination_Choice_Charrette_Participants.jpg "Destination Choice Content Charrette Participants, May 2017") 10 | 11 | - Vince Bernardin 12 | - Julie Dunbar 13 | - Eric Miller 14 | - Rolf Moeckel 15 | - Jeff Newman 16 | - Ram Pendyala 17 | - Rosella Picado 18 | - Jennifer Weeks 19 | 20 | The following pages were generated during this two day workshop: 21 | 22 | - [Destination Choice: Theoretical Foundations](Destination_Choice_Theoretical_Foundations) 23 | - [Choice Models with Aggregate Choices](Choice_Models_with_Aggregate_Choices) 24 | - [Destination Choice: Mathematical Formulation](Destination_Choice_Mathematical_Formulation) 25 | - [Destination Choice Set Formation](Destination_Choice_Set_Formation) 26 | - [Joint / Conditional Destination Choices](Joint__Conditional_Destination_Choices) 27 | - [Factors Affecting Destination Choice](Factors_affecting_destination_choice) 28 | - [Destination Choice: Data Sources](Destination_Choice_Data_Sources) 29 | - [Destination Choice: Parameter Estimation](Destination_Choice_Parameter_Estimation) 30 | - [Destination Choice: Calibration and Validation](Destination_Choice_Calibration_and_Validation) 31 | - [Destination Choice: Implementation and Application](Destination_Choice_Implementation_and_Application) 32 | - [Data Driven Methods](Data_Driven_Methods) 33 | - [Impedance](Impedance) 34 | - [Traffic Analysis Zone](Traffic_Analysis_Zone) 35 | -------------------------------------------------------------------------------- /topics/Current_trends_in_travel_behavior.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Current trends in travel behavior" 3 | categories: 4 | 5 | --- 6 | 7 | ### Effect of telecommuncations on travel behavior 8 | 9 | #### Telecommuting 10 | 11 | Commute distance, stress, and travel time were found in several studies to have a positive effect on teleworking, supporting the claim that the decision to work at home is based in part on distance to possible workplaces outside of the home [^1] [^2]. 12 | 13 | One study found that part-time employees tend to telecommute more than full-time employees[^3]. 14 | 15 | ### Housing Location Choices of Young Adults 16 | 17 | Recent studies have found trends of young adults preferring to live in more urban areas and travel shorter distances. 18 | 19 | #### References 20 | 21 | [^1]: Mokhatrian, P.L. and Ory, D.T. “The Impact of Teleworking on Commute Time, Distance, and Speed of California Workers”. University of California-Davis: 22 | 23 | [^2]: Helminen, V. and Ristimiki, M. “Relationships between Commuting Distance, Frequency, and Teleworking in Finland.” Journal of Transport Geography. Volume 15, Issue 5. September 2007 (331-342) 24 | 25 | [^3]: Yeraguntla, A. and Bhat, C. “Classification Taxonomy and Empirical Analysis of Work Arrangements.” Transportation Research Board. Transportation Research Record: Volume 1926: Jan 2005 26 | 27 | -------------------------------------------------------------------------------- /topics/DRCOG_s_Experience_Using_its_FOCUS_Activity_Based_Model.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "DRCOG's Experience Using its FOCUS Activity-Based Model" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models‏‎ 6 | - Resources 7 | - Webinars And Videos 8 | links: 9 | - type: Text File 10 | label: "Closed Caption Log" 11 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/DRCOG_ABM/Transcript.txt 12 | - type: PDF 13 | label: "Presentation Slides" 14 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/DRCOG_ABM/DRCOG_ABM_Webinar_Dec_13_2012.pdf 15 | - type: Text File 16 | label: "Questions and Answers" 17 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/DRCOG_ABM/QandA.txt 18 | --- 19 | 20 | 21 | 22 | 23 | 24 | Mr. Sabina and Mr. Rossi will discuss DRCOG’s Focus activity-based travel model, covering topics ranging from the development of the initial vision for the project, the design of the model’s theoretical and software structures, the calibration and validation of the model, to DRCOG’s uses of the model during the two years since completion of its initial version. 25 | 26 | #### Source 27 | 28 | [TMIP](TMIP) 29 | 30 | #### Presenters 31 | 32 | Erik Sabina, Denver Regional Council of Governments; 33 | Thomas Rossi, Cambridge Systematics 34 | 35 | #### Recorded Date 36 | 37 | 2012-12-13 38 | 39 | ------------------------------------------------------------------------ 40 | 41 | 42 | 43 | -------------------------------------------------------------------------------- /topics/DTA_Primer.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "DTA Primer" 3 | noTOC: true 4 | categories: 5 | - Dynamic Network Models 6 | - Reports 7 | - Resources 8 | --- 9 | 10 | 11 | *Resource Title* 12 | 13 | #### Author 14 | 15 | Yi-Chang Chiu, Jon Bottom, Michael Mahut, Alex Paz, Ramachandran Balakrishna, Travis Waller, Jim Hicks 16 | 17 | #### Source 18 | 19 | #### Abstract 20 | 21 | The objectives of this primer are to: 22 | • Explain the basic concepts of DTA and various DTA definitions and implementations, 23 | • Highlight the types of transportation analysis applications for which DTA models could be found useful, 24 | • Provide information about how to select a DTA model that best serves the intended application, 25 | • Provide information regarding planning for and executing a DTA traffic analysis activity, and 26 | • Describe the general DTA modeling procedure and modeling issues that may concern a model user. 27 | 28 | #### Copyright & Usage Permissions 29 | 30 | #### Publication Date 31 | 32 | 2011-6-1 33 | 34 | ------------------------------------------------------------------------ 35 | 36 | 37 | 38 | -------------------------------------------------------------------------------- /topics/Data_Visualization.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Data Visualization" 3 | categories: 4 | - Stub 5 | --- 6 | 7 | Data visualization in transportation concerns the visual display of information collected from transportation studies, or to convey information in support or evaluation of transportation policies. There is a great deal of overlap between transportation visualizations and the ideas and mechanics of data visualization more broadly, and this page is not designed to repeat information that is easily available in other places. The page can, however, serve as a "recipe book" for professionals looking for ideas or conventions in transportation visualizations. 8 | 9 | *This page is initially created as a summary of discussions at the 2017 Transportation Planning Applications Conference in Raleigh, North Carolina* 10 | 11 | Commonly Used Visualizations 12 | ---------------------------- 13 | 14 | Scatter Plots 15 | 16 | Bar Graphs/Histograms 17 | 18 | Network Bandwidth 19 | 20 | Regional Flow / Desire Lines 21 | 22 | Choropleth Maps 23 | 24 | New Trends in Visualization 25 | --------------------------- 26 | 27 | Interactivity 28 | 29 | Things to Avoid 30 | --------------- 31 | 32 | Pie Charts 33 | 34 | Chart Junk 35 | 36 | ADA-compliance 37 | 38 | -------------------------------------------------------------------------------- /topics/Design_Hourly_Volume.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Design Hourly Volume" 3 | categories: 4 | - Needs Review 5 | - Transportation Networks 6 | --- 7 | 8 | Design hourly volume (DHV) is the number of vehicles that travel through a segment of roadway during the design hour. The DHV is used for making roadway structural and capacity design decisions because traffic volume varies by hour and from day to day throughout the year. The formula for calculating the DHV is: 9 | 10 | DHV = K \* [AADT](Average_Annual_Daily_Traffic) 11 | 12 | Source: [NCHRP Report 765](NCHRP_Report_765) 13 | 14 | -------------------------------------------------------------------------------- /topics/DestChoice_MathFormulation_Fig-1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tfresource/tfresource-website/3bc6a3eec31aeec4699d196a6c5b4c05e358dd6b/topics/DestChoice_MathFormulation_Fig-1.jpg -------------------------------------------------------------------------------- /topics/Discussion_of_travel_delay_in_acceptable_models_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Discussion of travel delay in acceptable models in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Many travel models in the US calculate delays with a “volume-delay function” (VDF) where travel time on a link is a function of the volume on that same link. An example of a VDF is the well-known “BPR curve”. A much preferred method of calculating delays is to use operational analysis procedures from the “2010 US Highway Capacity Manual” or traffic network microsimulation models. Operational analysis procedures incorporate intersection geometry, signal timing and the effects of opposing and conflicting traffic. If a travel model calculates delays with a VDF, exclusively, then the estimated travel times (or speeds) must be viewed with suspicion, even when the model has been intensively calibrated and can show strong validation statistics. In addition, estimated turning movements will tend to have larger errors when delays are calculated with a VDF. Refinement steps are required when using speed and turning movement results for a project-level forecast from a travel model that depends upon VDFs for travel time estimation. 8 | 9 | References 10 | ---------- 11 | 12 | -------------------------------------------------------------------------------- /topics/Dynamic_network_models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Dynamic network models" 3 | categories: 4 | - Topic Circles 5 | - Network Assignment 6 | --- 7 | 8 | See [Dynamic Traffic Assignment](Dynamic_Traffic_Assignment). 9 | -------------------------------------------------------------------------------- /topics/Errors_and_variability_in_volume_data_for_project_level_traffic_forecasts.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Errors and variability in volume data for project-level traffic forecasts" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to the [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | [NCHRP Report 765](NCHRP_Report_765) reviewed literature about variability in traffic volume ([Average Daily Traffic](Average_Daily_Traffic), or ADT) data. Although there were disagreements between studies as to methodology and results, the following equation, expressing the consensus of these studies, should be used for highway projects. 11 | 12 | $$CV=\frac { 1.5 }{ { V }_{ }^{ 0.27 } }$$ 13 | 14 | where CV is the coefficient of variation (or the ratio of standard error to the mean) and V is the ADT. 15 | 16 | Figure: example with ADT=1,000 to 50,000 17 | 18 | ![|left|](CoefficientOfVariation.PNG "|left|") 19 | 20 | References 21 | ---------- 22 | 23 | -------------------------------------------------------------------------------- /topics/Explaining_Activity_Based_Models_to_a_General_Audience.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Explaining Activity-Based Models to a General Audience" 3 | categories: 4 | - Activity Based Models 5 | --- 6 | 7 | Travel model results often require additional interpretation and explanation to a non-technical audience. Because [activity-based models](Activity_Based_Models) are costly to implement and explain it is important to carefully convey how their functionality differs from other methods 8 | 9 | Here are some ways that modelers have successfully explained activity-based models: 10 | 11 | - Develop novel visual plots and animations that explain the outputs. The graphic below shows modelled vehicle miles traveled per person by home parcel in Seattle. Prepare a comparable graphic using a trip based model and demonstrate the value of the added precision. Examples of video animations can be found at [www.youtube.com/ARCModeling](http://www.youtube.com/ARCModeling) 12 | 13 | ![400 px|Modelled Vehicle Miles Traveled per Person by Home Parcel in Seattle](VMTperCapitaSeattle.jpg "400 px|Modelled Vehicle Miles Traveled per Person by Home Parcel in Seattle") 14 | 15 | - Compare to a familiar videogame simulation. Explain how a game, such as SimCity, evolves based on decisions made by the player. 16 | 17 | 18 | 19 | - Translate the model results into a familiar story. Follow the day in the life of one your model residents to show how the model is synthesizing actual choices. 20 | 21 | ------------------------------------------------------------------------ 22 | -------------------------------------------------------------------------------- /topics/External_surveys.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "External surveys" 3 | categories: 4 | - Travel Surveys 5 | --- 6 | 7 | ## Introduction to External Surveys 8 | 9 | The [Travel Survey Manual Chapter 15](https://trbtsm.wiki.zoho.com/Chapter-15-2.html) details the methods used to conduct roadside surveys. That practice has transitioned to using blue tooth, RFID and other technologies to track vehicle movements more safely than stopping vehicles and Chapter 15 concludes with links to resources that discuss these newer methods. 10 | 11 | In addition to directly collecting external travel, commercially available data sets are now available to supplement or complement survey data. These data sets compile data from cellular phone providers, in-vehicle GPS, and cell phone GPS to provide details of movements in, out and through regions. 12 | 13 | This short introduction was authored by Stacey Bricka. 14 | 15 | ## References 16 | - Everett J, Ruegg S, & Tardiff R. [Travel Survey Manual, Chapter 15](https://trbtsm.wiki.zoho.com/Chapter-15-2.html). 17 | -------------------------------------------------------------------------------- /topics/GPS_Based_Pilot_Survey_of_Freight_Movements_in_the_Midwest_Region.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "GPS Based Pilot Survey of Freight Movements in the Midwest Region" 3 | noTOC: true 4 | categories: 5 | - Freight Modeling 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "GPS Based Pilot Survey of Freight Movements in the Midwest Region" 11 | url: https://pdfs.semanticscholar.org/6cae/de96cce6ab9e8d3b15b4c0a312b5d1c6453a.pdf 12 | --- 13 | 14 | 15 | #### Author 16 | 17 | Kouros Mohammadian, Kazuya Kawamura, Karl Sturm, Zahra Pourabdollahi 18 | 19 | #### Source 20 | 21 | Project completed for USDOT’s RITA by CFIRE. 22 | 23 | #### Abstract 24 | 25 | The information presented here has been collected through the cooperation of a major Illinois based grocery chain with their headquarters and distribution center located in the Chicago region. The research team used the digital log files extracted from GPS tracking devices and the driver logs filled out during distribution tours as part of the analysis. The research team cleaned, processed, analyzed, and summarized this data. 26 | 27 | In this study, the research team did not require the participant’s truck drivers to do anything. Even without driver logs or written surveys, the GPS devices collected a great deal of information that the research team used to make behavioral inferences. Logistical decisions and behavior gleaned from this collected GPS data included destination choice, route choice, time-of-day choice, and trip length. 28 | 29 | #### Copyright & Usage Permissions 30 | 31 | Public Domain 32 | 33 | #### Publication Date 34 | 35 | April 1, 2013 Final Draft 36 | 37 | ------------------------------------------------------------------------ 38 | 39 | 40 | 41 | -------------------------------------------------------------------------------- /topics/Goods_Movement_Study_in_Illinois_Application_to_Freight_Transportation_and_Logistics.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Goods Movement Study in Illinois: Application to Freight Transportation and Logistics" 3 | noTOC: true 4 | categories: 5 | - Freight Modeling 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "Full Document Goods Movement Study in Illinois: Application to Freight Transportation and Logistics" 11 | url: https://www.ideals.illinois.edu/handle/2142/45785 12 | --- 13 | 14 | "Goods Movement Study in Illinois: Application to Freight Transportation and Logistics" 15 | 16 | #### Author 17 | 18 | Kouros Mohammadian, Karl Sturm, Zahra Pourabdollahi, and Amir Samimi 19 | 20 | #### Source 21 | 22 | Illinois Center for Transportation 23 | 24 | #### Abstract 25 | 26 | This report details the results generated by a nationwide online freight establishment study. 27 | The survey was assembled with the intention of allowing the formulation or enhancement of new or existing 28 | freight-demand microsimulation models. Within this report is an overview of the steps taken in designing and 29 | implementing the establishment and shipment questionnaires of the freight survey. Following that is a 30 | descriptive analysis of the results of key questions posed in our survey. Over the course of the study, 966 usable 31 | establishment surveys and 1,844 shipment forms were collected and assembled in a database, an adequate 32 | number for modeling purposes. 33 | 34 | #### Copyright & Usage Permissions 35 | 36 | Public Domain 37 | 38 | #### Publication Date 39 | 40 | March 2013 41 | 42 | ------------------------------------------------------------------------ 43 | 44 | 45 | 46 | -------------------------------------------------------------------------------- /topics/H_GAC_Activity_Based_Model_Model_Validation_Plan_Report.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "H-GAC Activity-Based Model – Model Validation Plan Report" 3 | noTOC: true 4 | categories: 5 | - Model Calibration And Validation 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "Report PDF" 11 | url: http://old.tfresource.org/images/5/59/H-GAC_ABM-Model_Validation_Plan.Final.pdf 12 | --- 13 | 14 | #### Author 15 | 16 | Cambridge Systematics, Inc. 17 | 18 | #### Source 19 | 20 | [TMIP](TMIP) 21 | 22 | #### Abstract 23 | 24 | This document provides direction for validation of the Houston-Galveston Area Council (H-GAC) Activity-Based Model (ABM). The development of this validation plan and the validation procedures and recommendations presented herein are based on guidance provided in the recently published Travel Model Improvement Program Travel Model Validation and Reasonableness Checking Manual – Second Edition1 (Validation Manual). Information from the Federal Transit Administration (FTA) Section 5309 New Starts guidance is also considered in the development of this validation plan. 25 | 26 | #### Copyright & Usage Permissions 27 | 28 | provided by Cambridge Systematics, Inc. with permission from H-GAC 29 | 30 | #### Publication Date 31 | 32 | August 2013 33 | -------------------------------------------------------------------------------- /topics/High_Occupancy_Toll_Lanes_Potential_for_Implementation_in_the_Atlanta_Region.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "High Occupancy Toll Lanes: Potential for Implementation in the Atlanta Region" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Papers 7 | - Resources 8 | links: 9 | - type: Paper (PDF) 10 | label: "High Occupancy Toll Lanes: Potential for Implementation in the Atlanta Region" 11 | url: http://www.georgiatolls.com/assets/docs/HOT_Final_Report.pdf 12 | --- 13 | 14 | 15 | *Resource Title* 16 | 17 | #### Author 18 | 19 | Parsons Brinckerhoff 20 | 21 | #### Source 22 | 23 | Prepared for: Georgia State Road and Tollway Authority 24 | 25 | #### Abstract 26 | 27 | This study examined the feasibility of introducing high occupancy toll (HOT) lanes in the Atlanta road network as a method to provide safe reliable trips throughout the region and to maximize the use of the current and future high occupancy vehicle (HOV) system. The study was in response to Georgia Senate Resolution (SR) 575 that requested “a comprehensive study of the feasibility of implementing HOT lanes along the highways of the metropolitan Atlanta area and implementing HOV and HOT lanes along the GA 400 Corridor.” 28 | 29 | #### Copyright & Usage Permissions 30 | 31 | #### Publication Date 32 | 33 | 2005-4-1 34 | 35 | ------------------------------------------------------------------------ 36 | 37 | 38 | 39 | -------------------------------------------------------------------------------- /topics/Ideal_travel_model_standard_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Ideal travel model standard in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | The “travel model ideal” was defined in NCHRP Report 765. The purpose of the “travel model ideal” was to provide a goal for model developers and to alert practitioners that travel models can satisfy the needs of project-level forecasts, under many circumstances. The ["Best practical experience model standard"](Best_practical_experience_model_standard_in_project_level_traffic_forecasting) is a more realistic design for travel models in many states that may be used for project-level travel forecasting. 8 | 9 | References 10 | ---------- 11 | 12 | -------------------------------------------------------------------------------- /topics/Innovations_in_Travel_Modeling.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Innovations in Travel Modeling" 3 | categories: 4 | - Topic Circles 5 | --- 6 | 7 | 8 | 9 | The Innovations in Travel Modeling (ITM) conference series is the premier forum for sharing the latest developments in travel modeling, networking with fellow professionals, and identifying research and implementation challenges and issues associated with deploying cutting-edge computational methods to meet evolving planning contexts. There have been six conferences so far in the series, with the seventh coming up in June 2018 in Atlanta, Georgia. 10 | 11 | - [1st ITM Conference, Austin, Texas (2006)](1st_TRB_Conference_on_Innovations_in_Travel_Modeling) 12 | - [2nd ITM Conference, Portland, Oregon (2008)](2nd_TRB_Conference_on_Innovations_in_Travel_Modeling) 13 | - [3rd ITM Conference, Tempe, Arizona (2010)](3rd_TRB_Conference_on_Innovations_in_Travel_Modeling) 14 | - [4th ITM Conference, Tampa, Florida (2012)](http://www.cvent.com/events/4th-transportation-research-board-conference-on-innovations-in-travel-modeling-itm-/event-summary-092a2bae88ec4d3e8c752667802ba215.aspx) 15 | - [5th ITM Conference, Baltimore, Maryland (2014)](http://www.cvent.com/events/innovations-in-travel-modeling/event-summary-477f7b8596454859ac120f90d9ebc56c.aspx) 16 | - [6th ITM Conference, Denver, Colorado (2016)](6th_ITM_Conference_Denver_Colorado_2016) 17 | - [7th ITM Conference, Atlanta, Georgia (2018)](7th_ITM_Conference_Atlanta_Georgia_2018) 18 | 19 | Each conference attempts to further build on the successes of the previous conferences to serve as a venue for the modeling community to exchange information on promising modeling methods to address emerging policy questions. 20 | 21 | -------------------------------------------------------------------------------- /topics/Inside_the_Black_Box.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Inside the Black Box" 3 | noTOC: true 4 | categories: 5 | - Reports 6 | - Resources 7 | links: 8 | - type: PDF 9 | label: "Full Document" 10 | url: https://www4.uwm.edu/cuts/blackbox/blackbox.pdf 11 | - type: PDF 12 | label: "Modeling Primer" 13 | url: http://www4.uwm.edu/cuts/utp/models.pdf 14 | --- 15 | 16 | _Inside the Black Box: Making Transportation Models Work for Livable Communities_ 17 | 18 | #### Authors 19 | 20 | - Edward Beimborn 21 | - Rob Kennedy 22 | - William Schaefer 23 | 24 | #### Source 25 | 26 | - Citizens for a Better Environment 27 | - Environmental Defense Fund (Publication 99215S) 28 | 29 | #### Abstract 30 | 31 | A classic document that explains the transportation planning process in simple terms, along with the interaction between transportation planning and travel forecasting. It was originally prepared in 1995 and subsequently updated in 2006. 32 | 33 | This primer is intended to explain how the process works, the assumptions made and the steps that are used in urban transportation planning. This is done in order to help more people understand the process and its implications and to help people to interpret and comment on its results. This primer is divided into two sections, an overview of transportation planning in general - the what, why, who and how of transportation planning and a more specific description of the actual models used to forecast future travel. Since the basic purpose of transportation planning is to answer questions about future travel, the primer will use a question and answer format to explain how transportation planning takes place. 34 | 35 | ### Publication Date 36 | 37 | 2006-06-01 38 | -------------------------------------------------------------------------------- /topics/Land_use_models_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Land use models in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Objectives 8 | ---------- 9 | 10 | Several major metropolitan areas in the US have integrated land-use models into their travel forecasts. The latest generation of land-use models require extensive and spatially-detailed data on the economy of the region. A well-functioning land-use model will forecast the spatial distribution of population and employment by economic sector. 11 | 12 | Guidelines 13 | ---------- 14 | 15 | These models are expensive and time-consuming to set up and calibrate. Land-use models are especially important for regions that are rapidly developing and are testing major alternatives to greatly improve highway and transit accessibility to parts of the region that are now less intensively developed. However, land-use models have not undergone the level of validation as have traditional four-step travel forecasting models, so there is still considerable uncertainty in the planning community as to the quality of those forecasts. It is very important that an analyst be advised by outputs of land-use models, where available, but land-use models are of only limited value for project-level travel forecasting. 16 | 17 | -------------------------------------------------------------------------------- /topics/Location_Based_Services_Data.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Location-Based Services Data" 3 | categories: 4 | --- 5 | 6 | Location-based Service (LBS) data is aggregated from smartphone and other mobile device applications (“apps”). LBS data is not based on a single technology such as cell-tower signaling or GPS; rather, these data represent the best location available to mobile apps at a particular point in time, which could come from GPS, Wi-Fi or Bluetooth beacons, or cell-tower signaling under various circumstances (although its reliance on the last is limited). LBS data is the newest type of origin-destination (OD) [big data](Big_Data) and has only recently become available for widespread use in transportation analysis as of 2017. 7 | 8 | ### Precision 9 | 10 | In contrast to cell-based data, LBS data offers better spatial precision, although its resolution is less than that of GPS data. Locational precision is claimed to be between 10 and 100 meters, with most data observations precise to better than 50 meters. 11 | 12 | ### Sample Penetration 13 | 14 | Sample penetration can vary by region due in part to the varying popularity of apps in different markets. However, sample penetration is expected to be less variable than in cell-based data given the large number of apps LBS draws on. Some studies have found LBS data to include 5–8% of the vehicles in a corridor drawn from observations of up to 15% of the population. LBS data is often provided for multiple months, increasing the overall sample size and offsetting slightly lower penetration rates compared to cellular data. 15 | 16 | ### Device Identifier Persistence 17 | 18 | Like cell-based data and unlike most GPS data, LBS data have longer term device ID persistence. This can be used both to correct for demographic biases using imputed residence locations and to support long-distance and visitor travel analyses. 19 | -------------------------------------------------------------------------------- /topics/Long_range_transportation_plan.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Long range transportation plan" 3 | categories: 4 | 5 | --- 6 | 7 | **Long Range Transportation Plan** 8 | "A document resulting from regional or statewide collaboration and consensus on a region or state's transportation system, and serving as the defining vision for the region's or state's transportation systems and services. In metropolitan areas, the plan indicates all of the transportation improvements scheduled for funding over the next 20 years." - [FHWA](https://www.fhwa.dot.gov/planning/glossary/glossary_listing.cfm?TitleStart=L) 9 | 10 | Long-range transportation plans take place at a variety of geographic levels: 11 | 12 | - Statewide, conducted by State DOTs 13 | - Regional, a key function of [Metropolitan Planning Organizations](Metropolitan_Planning_Organization) 14 | - Local, less common, but can be conducted by counties, cities, or other local jurisdictions 15 | 16 | ## References 17 | 18 | 19 | 20 | ------------------------------------------------------------------------ 21 | 22 | -------------------------------------------------------------------------------- /topics/MPO_model_documentation.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "MPO model documentation" 3 | categories: 4 | --- 5 | 6 | # Summary 7 | 8 | Planning agencies generally produce documentation for their regional travel demand models that outline the structure of the model along with the model calibration report, though the two may be separate documents. 9 | 10 | # References and examples of MPO documentation 11 | 12 | [Atlanta Regional Commission](https://atlantaregional.org/transportation-mobility/modeling/modeling/) 13 | 14 | [Chicago Metropolitan Agency for Planning](https://www.cmap.illinois.gov/data/transportation/modeling) 15 | 16 | [Metropolitan Washington Council of Governments](https://www.mwcog.org/transportation/data-and-tools/modeling/model-documentation/) 17 | 18 | [Metropolitan Transportation Commission](https://github.com/BayAreaMetro/modeling-website/wiki) (San Francisco) 19 | 20 | [New York Metropolitan Transportation Council](https://www.nymtc.org/Data-and-Modeling/New-York-Best-Practice-Model-NYBPM) 21 | 22 | [North Central Texas Council of Governments](https://www.nctcog.org/trans/data/tdm) (Dallas-Fort Worth) 23 | 24 | [Portland Metro](https://www.oregonmetro.gov/sites/default/files/2015/04/16/trip-based_travel_demand_model_methodology.pdf) 25 | 26 | [Puget Sound Regional Council](https://www.psrc.org/activity-based-travel-model-soundcast) (Seattle) 27 | 28 | [Sacramento Area Council of Governments](https://www.sacog.org/modeling) 29 | 30 | [Southern California Association of Governments](http://www.scag.ca.gov/DataAndTools/Pages/DataTools/Modeling.aspx) (Los Angeles) 31 | -------------------------------------------------------------------------------- /topics/Markov_Models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Markov Models' 3 | categories: 4 | - Land Use Transport Modeling 5 | --- 6 | 7 | ## Introduction 8 | Markov transition (chain) models are used within land use models to model non-spatial events such as: 9 | - Household socio-demographic changes (except household relocation) 10 | - Real estate renovation and deterioration 11 | - Firmographic changes (except firm relocation) 12 | 13 | The use of Markov transition models within land use models is discussed in more detail [here](Design_principles_of_land_use_models). 14 | 15 | Please see the following external resources for more general information on Markov transition models. 16 | 17 | ## Resources 18 | - For a visual demo of Markov transition models, see 19 | - For a more detailed explanation of Markov transition models, see 20 | -------------------------------------------------------------------------------- /topics/Measures_of_effectiveness_and_performance_measures_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Measures of effectiveness and performance measures in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Guidelines 8 | ---------- 9 | 10 | Measures of effectives (MOEs) are direct outputs of travel models to gauge the amount of travel for an alternative and to understand the alternative’s impacts. Performance measures relate directly to transportation plan objectives and give an indication about whether the plan’s objectives and goals are being attained, once implemented. Performance measures should preferably be calculated from real-world data. It is possible for a travel forecasting model and its post-processors to compute MOEs that resemble performance measures. This section will deal mainly with MOEs. 11 | Standard MOEs from travel models include vehicle-hours-travel and vehicle-miles-traveled. These two MOEs may be broken out by functional class and/or by location. Other easily computed MOEs are total hours of delay and average speed. Travel models may also be able to roughly estimate air pollution emissions from vehicles, greenhouse gas emissions, and fuel consumption. 12 | 13 | Caution needs to be exercised when interpreting MOEs because travel models do not encompass all possible behavioral responses by travelers. For example, a travel model might suggest that fuel consumption would decline with a lowering of delays at signals. However, if the travel model does not include feedback to the distribution step or if the travel model does not include a land-use component, then offsetting increases in trip length owing to reduced delays at signals would not have been accounted for in the total fuel consumptions estimates. 14 | 15 | References 16 | ---------- 17 | 18 | -------------------------------------------------------------------------------- /topics/Modal_hierarchy.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Modal hierarchy" 3 | categories: 4 | --- 5 | 6 | Modal hierarchy is useful in being able to "name" the "main mode" that a person has taken when they have taken multiple modes to complete a trip. 7 | 8 | An example modal hierarchy could be: 9 | 10 | 1. Subway 11 | 2. Express Bus 12 | 3. Local Bus 13 | 14 | If an individual did the following to get from O --> D, using the hierarchy above, Subway would be the *main mode*, and the choice that this would fall under in the mode choice model would be *Kiss and Ride to Subway* even though the drop-off occurred at the express bus station. 15 | 16 | - Got dropped off at bus station 17 | - Express Bus to downtown 18 | - Walked from bus station to subway station 19 | - Took subway across town 20 | - Walked from subway to destination 21 | 22 | ------------------------------------------------------------------------ 23 | 24 | -------------------------------------------------------------------------------- /topics/Model_calibration.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Model calibration" 3 | categories: 4 | --- 5 | 6 | 7 | Model calibration is the adjustment of constants and other model parameters in estimated or asserted models in an effort to make the models replicate observed data for a base year or otherwise produce more reasonable results 8 | -------------------------------------------------------------------------------- /topics/Model_integration.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Model integration" 3 | categories: 4 | - Topic Circles 5 | - Stub 6 | --- 7 | 8 | 9 | 10 | Placeholder page. 11 | -------------------------------------------------------------------------------- /topics/Model_validation_plans.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Model validation plans" 3 | categories: 4 | - Activity Based Models 5 | - Model Calibration And Validation 6 | - Stub 7 | - Trip Based Models 8 | --- 9 | 10 | Summary 11 | ------- 12 | 13 | Model validation plans are used to guide the model validation process. They should typically be developed in conjunction with a model development plan. The purposes for a model validation plan include: 14 | 15 | - Ensuring that all model steps are validated 16 | 17 | : 18 | 19 | - Identifying validation data that will be required 20 | 21 | [^1] 22 | 23 | ------------------------------------------------------------------------ 24 | 25 | [^1]: Houston-Galveston Area Council Activity-Based Model Validation Plan 26 | 27 | -------------------------------------------------------------------------------- /topics/Modelers.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Modelers" 3 | categories: 4 | --- 5 | 6 | >The content on this page is derived from notes that were taken during the Modeling Meta session at the 2014 Innovations in Travel Modeling Conference in Baltimore. 7 | 8 | Finding and training great modelers is always a challenge: both at consulting firms and at public agencies. The skill set required to be a great modeler is in high demand in other industries and it can be difficult to compete. 9 | 10 | Recruitment Techniques 11 | ---------------------- 12 | 13 | - Make pay scale competitive with other industries that require a similar skillset 14 | - Save [TMIP listserv](http://www.fhwa.dot.gov/planning/tmip/community/list_serv.cfm) postings with salaries for other modeling positions 15 | - Look up other job listings with same skill-set 16 | - Make position name alluring 17 | - *Analyst* is not as exciting as *Data Scientist* or *Predictive Analytics Guru* 18 | 19 | Desired Skill Set 20 | ----------------- 21 | 22 | - Common sense 23 | - Analytical mind 24 | - Proficiency with at least one statistical analysis tool 25 | - Proficiency with at least one programming tool 26 | - Desire to help society 27 | - Desire to be a travel modeler 28 | 29 | Degrees 30 | ------- 31 | 32 | The most common degree for travel modelers is transportation/civil engineering. However, **many** successful modelers have come from other degrees. Many travel modelers do have a graduate degree. Common degrees include: 33 | 34 | - Civil / Transportation Engineering 35 | - City and Regional Planning (paired with a more quantitative degree) 36 | - Urban Studies (paired with a more quantitative degree) 37 | - Computer Science 38 | - Physics 39 | - Mathematics 40 | - Statistics 41 | -------------------------------------------------------------------------------- /topics/NCHRP_Report_765.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "NCHRP Report 765" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | - Reports 7 | - Resources 8 | --- 9 | 10 | Analytical Travel Forecasting Approaches for Project-Level Planning and Design 11 | ------------------------------------------------------------------------------ 12 | 13 | [TRB’s National Cooperative Highway Research Program (NCHRP) Report 765: Analytical Travel Forecasting Approaches for Project-Level Planning and Design](http://www.trb.org/main/blurbs/170900.aspx) describes methods, data sources, and procedures for producing travel forecasts for highway project-level analyses. This report provides an update to [NCHRP Report 255: Highway Traffic Data for Urbanized Area Project Planning and Design](http://teachamerica.com/tih/PDF/nchrp255.pdf). 14 | 15 | In addition to the report, **Appendices A** through **I** from the contractor’s final report are available on a "disc image file" that can be downloaded from [CRP-CD-143](http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_765.iso). These appendices supplement this report by providing a substantial amount of companion data and information. The appendices also include the extended literature review, the detailed NCHRP Report 255 review, supplementary tables, a list of defined acronyms, and a glossary. Also included on CRP-CD-143 are spreadsheet demonstrations, and, for reference purposes, a tool developed by the North Carolina Department of Transportation to assess annual average daily traffic. 16 | 17 | Published by TRB in 2014. 18 | 19 | The content of this report is covered extensively within this wiki under the topic: [Project-level traffic forecasting](Project_level_traffic_forecasting). 20 | 21 | -------------------------------------------------------------------------------- /topics/National_guidelines_for_use_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "National guidelines for use in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | National guidelines for project level traffic forecasts are provided in [NCHRP Report 765](NCHRP_Report_765). In many cases, an approved technique for projects in Hawaii is explained fully in this NCHRP report. NCHRP Report 255 has been superseded. 11 | 12 | In the absence of local forecasting parameters, it is acceptable to substitute national transferable parameters from one of these documents: 13 | 14 | - “Travel Estimation Techniques for Urban Planning,” [NCHRP Report 365](http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_365.pdf); 15 | - “Travel Demand Forecasting Parameters and Techniques,” [NCHRP Report 716](http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_716.pdf); or 16 | - “Long-Distance and Rural Travel. Transferable Parameters for Statewide Travel. Forecasting Models,” [NCHRP Report 735](http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_735.pdf). 17 | 18 | Certain techniques mentioned in these topics make specific reference to data tables from these documents. These documents also provide data for reasonableness checks of locally derived parameters. 19 | 20 | -------------------------------------------------------------------------------- /topics/On_Board_Transit_Survey.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "On Board Transit Survey" 3 | categories: 4 | - Travel Survey Data 5 | - Stub 6 | --- 7 | 8 | 9 | A survey of transit riders. 10 | 11 | Types: 12 | 13 | - Personal Interview 14 | 15 | Common Uses in Travel Modeling: 16 | 17 | - Validate route building parameters 18 | 19 | Relevant Resources: 20 | 21 | - [TCRP Synthesis 63](TCRP_Synthesis_63) 22 | - [Travel Survey Manual Wiki Chapter 16](http://www.travelsurveymanual.org/Chapter-16.html) 23 | 24 | ------------------------------------------------------------------------ 25 | -------------------------------------------------------------------------------- /topics/Open_Code_Directory.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Open Code Directory" 3 | noTOC: true 4 | categories: 5 | - Reports 6 | - Resources 7 | links: 8 | - type: Website 9 | label: "Link" 10 | url: https://zephyrtransport.github.io/zephyr-directory/ 11 | --- 12 | 13 | 14 | *Zephyr Open Source Code Directory* 15 | 16 | ### [Zephyr Open Source Code Directory](https://zephyrtransport.github.io/zephyr-directory) 17 | 18 | #### Source 19 | 20 | [Zephyr Foundation](http://zephyrtransport.org) 21 | 22 | #### Summary 23 | 24 | This website is a directory of open-source software and code snippets that could be broadly helpful to the transportation analysis community. 25 | In addition, it has articles to help people use, contribute, and manage open source code projects. 26 | 27 | #### Support 28 | 29 | The creation of the Zephyr Directory was made possible with the support of the Ohio Department of Transportation. 30 | 31 | #### Creation Date 32 | 33 | 2017-4-17 34 | 35 | ------------------------------------------------------------------------ 36 | -------------------------------------------------------------------------------- /topics/Origin_Destination.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Origin-Destination" 3 | categories: 4 | - Needs Review 5 | - Spatial Data 6 | - Stub 7 | - Transportation Networks 8 | - Trip Based Models 9 | --- 10 | 11 | An **Origin-Destination** pair (commonly referred to as OD pair) is commonly used to model trips between two locations. 12 | 13 | Summary 14 | ------- 15 | 16 | ------------------------------------------------------------------------ 17 | 18 | -------------------------------------------------------------------------------- /topics/Path_Choice_Mode_choice_Consistency.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Path Choice and Mode Choice Consistency" 3 | categories: 4 | - Choice Models 5 | - Mode Choice 6 | --- 7 | 8 | It is important to consider the consistency in parameters used for path choice and [mode choice](Mode_choice). If they are not relatively similar, your model will produce unintuitive results. 9 | 10 | For Example: 11 | 12 | ### Path Building 13 | 14 | If the path building step weights access time the same as in-vehicle time, then Route A is found to be much better than Route B and in the route evaluation step, it will use the costs found from Route A. 15 | 16 | ``` 17 |           Access Time (1x)    +   In-Vehicle Time (1x)   =  Total Gen. Cost 18 | Route A       5 x 1 =  5            1 x 1 = 1           =  6 19 | Route B       1 x 1 =  1            8 x 1 = 8         =  9 20 | ``` 21 | 22 | ### Mode Choice 23 | 24 | ...but if the mode choice model actually takes into account that people don't like waiting and walking so much as they like riding, Route B looks like the better deal. 25 | 26 | ``` 27 |           Access Time (2x)    +   In-Vehicle Time (1x)  =  Total Gen. Cost 28 | Route A       5 x 2 = 10            1 x 2 = 2           =  12 29 | Route B       1 x 2 =  2            8 x 1 = 8         =  10 30 | ``` 31 | 32 | One of the possible outcomes of this is that you could actually make improvements to the transit network, but they would result in decreases in transit usage because they would be inconsistently evaluated. 33 | 34 | -------------------------------------------------------------------------------- /topics/Policy_relevance_of_transportation_models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Policy relevance of transportation models" 3 | categories: 4 | 5 | --- 6 | 7 | Summary 8 | ------- 9 | 10 | Transportation models, at least in the context of metropolitan-level planning, are implemented to inform decision-makers on a variety of issues. Modeling efforts are not, or should not be, undertaken in a vacuum without consideration of the ultimate use of the model. 11 | 12 | Throughout most of their history, regional transportation models were designed to study the impacts of the provision of road and highway infrastructure on regional mobility. The early models were eventually upgraded to include the ability to forecast transit as well as auto modes. 13 | 14 | ------------------------------------------------------------------------ 15 | 16 | -------------------------------------------------------------------------------- /topics/Population_Synthesis_For_Microsimulating_Travel_Behavior.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Population Synthesis For Microsimulating Travel Behavior" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models 6 | - Papers 7 | - Resources 8 | links: 9 | - type: Paper (PDF) 10 | label: "Link" 11 | url: http://www.caee.utexas.edu/prof/bhat/ABSTRACTS/SPG_Guo_Bhat.pdf 12 | --- 13 | 14 | 15 | #### Author 16 | 17 | Jessica Y. Guo and Chandra R. Bhat 18 | 19 | #### Source 20 | 21 | www.caee.utexas.edu 22 | 23 | #### Abstract 24 | 25 | For the purpose of activity-based travel demand forecasting, the representativeness of the base year synthetic population is critical to the accuracy of subsequent simulation outcomes. To date, the conventional approach for synthesizing the base year population is based on the methodology first developed by Beckman et al. (1996). In this paper, we discuss two issues associated with this conventional approach. The first issue is often termed as the zero-cell-value problem, and the second issue is related to the inability to control for statistical distributions of both household and individual-level attributes. We then present a new population synthesis procedure that addresses the limitations of the conventional approach. The new procedure is implemented into an operational software system and is used to generate synthetic populations for the Dallas/Fort-Worth area in Texas. Our validation results show that, compared to the conventional approach, the new procedure produces a synthetic population that more closely represents the true population. 26 | 27 | #### Copyright & Usage Permissions 28 | 29 | #### Publication Date 30 | 31 | 2007 32 | 33 | ------------------------------------------------------------------------ 34 | 35 | 36 | 37 | -------------------------------------------------------------------------------- /topics/Pricing_and_Travel_Time_Reliability_Enhancements_in_the_SANDAG_Activity_Based_Travel_Model_Final_Report.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Pricing and Travel Time Reliability Enhancements in the SANDAG Activity-Based Travel Model: Final Report' 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Activity Based Models 7 | - Pricing And Valuation 8 | - Reports 9 | - Resources 10 | links: 11 | - type: Report (PDF) 12 | label: 'Link' 13 | url: SANDAG_C04Report.pdf 14 | --- 15 | 16 | #### Author 17 | 18 | RSG 19 | 20 | #### Source 21 | 22 | #### Abstract 23 | 24 | Final Report from the SHRP2 C04 Project with San Diego Association of Governments (SANDAG) 25 | 26 | #### Copyright & Usage Permissions 27 | 28 | #### Publication Date 29 | 30 | 2016-6-30 31 | 32 | --- 33 | -------------------------------------------------------------------------------- /topics/Project_level_forecasting_process.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Project-level forecasting process" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | Requesting a forecast 11 | --------------------- 12 | 13 | The form shown below may be used for requesting a forecast and is typical. The request must contain the following information (adapted from the [“Ohio Certified Traffic Manual”](http://www.dot.state.oh.us/Divisions/Planning/SPR/ModelForecastingUnit/Documents/OH_Cert_Traffic_Manual.pdf) and Hawaii’s “Traffic Assignment Work Order” form): 14 | 15 | - Project identifier; 16 | - Description of the project; 17 | - Open-to-traffic year and design year; 18 | - Requested design values; 19 | - Other requirements; 20 | - Map(s) showing project limits; 21 | - List of intersections requiring turning movements, if any; 22 | - List of any other facilities needing special attention; 23 | - Required time periods of analysis (24 hours, PM peak hour, etc.); 24 | - Details of planned developments or other known factors which may impact the project; and 25 | - Need by date. 26 | 27 | ![](TrafficForecastRequestFormPage1.jpg "TrafficForecastRequestFormPage1.jpg") 28 | 29 | ![](TrafficForecastRequestFormPage2.jpg "TrafficForecastRequestFormPage2.jpg") 30 | 31 | Forecasting process flow diagram 32 | -------------------------------- 33 | 34 | The figure below summarizes the major steps in the project-level traffic forecasting process. 35 | 36 | ![](ProjectLevelProcess.jpg "ProjectLevelProcess.jpg") 37 | 38 | References 39 | ---------- 40 | 41 | -------------------------------------------------------------------------------- /topics/Puget_Sound_Regional_Council.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Puget Sound Regional Council" 3 | categories: 4 | --- 5 | 6 | Summary 7 | ------- 8 | 9 | The Puget Sound Regional Council is the MPO for the four county Puget Sound Region. They have: 10 | 11 | - Activity Based Model 12 | - UrbanSim Land Use Model 13 | 14 | 15 | -------------------------------------------------------------------------------- /topics/Python_Test.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Python Integrated Sandbox' 3 | categories: 4 | --- 5 | 6 | here is an experimental Python code sandbox! 7 | 8 | 9 | 10 | ``` 11 | import os,sys,numpy 12 | 13 | # Turtles all the way down 14 | 15 | turtles = ['how many fingers am I holding up?'] 16 | print(turtles) 17 | 18 | ``` 19 | 20 | 21 | 22 | Did it work? 23 | -------------------------------------------------------------------------------- /topics/README.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Index' 3 | no_index: true 4 | editLink: false 5 | categories: 6 | - About 7 | --- 8 | 9 | The pages on ==TFR== are loosely divided into sections on models, data, practical applications/use cases, and a glossary. You can also refer to the [Table of Contents](00_Table_Contents.md). 10 | 11 | Browse below, or use the search box to find something specific. 12 | 13 | ::: tip START HERE 14 | If you're new to travel forecasting, read [The Big Picture](Big_Picture) first! 15 | ::: 16 | 17 | 18 | -------------------------------------------------------------------------------- /topics/Refining_speeds_for_evaluation_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Refining speeds for evaluation in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Guidelines 8 | ---------- 9 | 10 | Some post-processors used for evaluation require speeds at different times of day. Ideally, speeds should be estimated hour-by-hour within a travel model or by further analysis of hourly traffic volumes from another forecasting methodology. It is not possible to obtain hourly speeds directly from multihour (or 24-hour) forecasted volumes. If multihour speeds are needed, they should be calculated as the volume-weighted average of speeds across all hours in the time period. 11 | 12 | References 13 | ---------- 14 | 15 | -------------------------------------------------------------------------------- /topics/Regulatory_framework_for_metropolitan_modeling.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Regulatory framework for metropolitan modeling" 3 | categories: 4 | - Urban And Metropolitan Models 5 | --- 6 | 7 | Statutory regulations over regional transportation modeling comes primarily from two sources: the Clean Air Act Amendments of 1990 ([CAAA](http://www2.epa.gov/aboutepa/epa-history-clean-air-act-amendments-1990)) and federal transportation law, [ISTEA](http://ntl.bts.gov/DOCS/ste.html) and follow-up legislation [TEA-21](http://www.fhwa.dot.gov/tea21/sumcov.htm), [SAFETEA-LU](http://www.fhwa.dot.gov/safetealu/summary.htm) and [MAP-21](http://www.fhwa.dot.gov/map21/). The transportation legislation works together with the environmental framework established by CAAA to reduce air pollution in urbanized areas, to monitor the progress made towards reaching clean air targets, and to facilitate future improvements in regional air quality by reducing emissions from mobile sources. In practical terms, the later goal has required regional planning agencies to demonstrate that their long-range transportation investment strategy will improve and not degrade urban air quality, which in turn has required an upgrading in forecasting abilities at the regional level. 8 | 9 | ------------------------------------------------------------------------ 10 | 11 | -------------------------------------------------------------------------------- /topics/Reporting_of_reasonable_bounds_on_forecast_values_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Reporting of reasonable bounds on forecast values in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to the [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | Assessing Uncertainty 11 | --------------------- 12 | 13 | Scenario testing places bounds on the range of possible forecast values, given variations in future conditions. Within a single scenario, there is still the possibility of uncertainty in a forecast. The range of uncertainty in the forecasts can be established through validation statistics or, in the case of time series models, goodness-of-fit statistics such as the standard error of the estimate. 14 | 15 | The range of uncertainty should be reported consistently with the parameters of the extended [half-lane rule](Half_lane_rule_and_extensions_in_project_level_traffic_forecasting). The procedures for calculating the range of uncertainty will differ between techniques. For most projects, a 50% confidence interval should be used, which corresponds to the “probable error” of the forecast. 16 | 17 | Measures of Effectiveness (MOEs) 18 | -------------------------------- 19 | 20 | Aggregated results have comparatively less uncertainty than disaggregated results, due to cancelling of random errors. Therefore, the use of measures of effectiveness (MOEs) are encouraged to the extent that they provide useful information to the decision processes. MOEs include such items as vehicle-miles-traveled (VMT), vehicle-hours-traveled (VHT), average speed, percent delay and total fuel consumption. 21 | 22 | References 23 | ---------- 24 | 25 | -------------------------------------------------------------------------------- /topics/Reports.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Reports" 3 | categories: 4 | - Needs Review 5 | - Resources 6 | --- 7 | 8 | 9 | 10 | -------------------------------------------------------------------------------- /topics/Representations_of_Decision_Making_Behavior_in_Travel_Modeling.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Representations of Decision Making Behavior in Travel Modeling" 3 | categories: 4 | - Travel Behavior 5 | --- 6 | 7 | ### Rational Decision Making 8 | 9 | #### Random Utilty Maximization and Choice Modeling 10 | 11 | Some travel models depict travel behavior using [utility](utility) and [decision theories](http://en.wikipedia.org/wiki/Decision_theory). 12 | To learn more about how travel is represented with choice models see: [Choice Models](Choice_Models) 13 | 14 | #### Regret Minimization 15 | 16 | ### Satisficing Decison Making 17 | 18 | ### Cognitive Process Modeling 19 | 20 | ### Learning and Habit Formation 21 | 22 | ------------------------------------------------------------------------ 23 | 24 | -------------------------------------------------------------------------------- /topics/Resources.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Resources" 3 | categories: 4 | --- 5 | 6 | Welcome to the Resources section of the Travel Forecasting Resource. Do you have something that has been useful in your travel forecasting work? Please take a minute to create a Resource page and share it here! 7 | 8 | **How to create a Resource page you ask?** First, type the title of the Resource you are wanting to add into the Search box above (this will help us avoid having duplicate copies of the same thing posted to the website.) If the Search returns the name of your resource in 'red' text, that indicates the Resource page is not found. Next click on the 'red' link and you will be directed to create the page. Be sure to select and load the appropriate template from the drop down box when you are creating the page - you can choose from publications, presentations, papers and webinars. What -- your resource type isn't in this list?!? Please click on the 'Talk' button above and leave a note for the Administrators and [TF Resource Volunteers](TF_Resource_Volunteers) so additional resource types can be added to the list of options. 9 | 10 | Thank you for your interest in the Travel Forecasting Resource! 11 | 12 | -------------------------------------------------------------------------------- /topics/SFCTA_Paper_incorporating_crowding.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "SFCTA Paper incorporating crowding" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Papers 7 | - Resources 8 | links: 9 | - type: Paper (PDF) 10 | label: "Full Document" 11 | url: http://link_to_file 12 | --- 13 | 14 | 15 | *Incorporating crowding into the San Francisco activity-based travel model* 16 | 17 | #### Author 18 | 19 | Daniel Wu, Lisa Zorn, and Elizabeth Sall 20 | 21 | #### Source 22 | 23 | Published in [Transportation](http://link.springer.com/article/10.1007/s11116-012-9405-x) 24 | 25 | #### Abstract 26 | 27 | #### Copyright & Usage Permissions 28 | 29 | #### Publication Date 30 | 31 | 2012-July-1 32 | 33 | ------------------------------------------------------------------------ 34 | 35 | 36 | 37 | -------------------------------------------------------------------------------- /topics/SFCTA_s_Experience_Using_its_SF_CHAMP_Activity_Based_Model.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "SFCTA's Experience Using its SF-CHAMP Activity-Based Model" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models‏‎ 6 | - Resources 7 | - Webinars And Videos 8 | links: 9 | - type: Text File 10 | label: "Closed Caption Log" 11 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/SFCTA_ABM/Transcript.txt 12 | - type: PDF 13 | label: "Presentation Slides" 14 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/SFCTA_ABM/SFCTA_ABM_Webinar_Nov_15_2012.pdf 15 | - type: Text File 16 | label: "Questions and Answers" 17 | url: http://media.tmiponline.org/webinars/2012/TMIP_ABM_Webinars/SFCTA_ABM/QandA.txt 18 | --- 19 | 20 | 21 | 22 | 23 | 24 | Have you ever wondered what it's like to have an Activity-Based Model in your day-to-day toolbox... How many people does it really take? How big are the computers? What do you do with all of that data? How does it actually help decision-making? How hard are they to maintain? How do you deal with all that code? The first half of the session will focus on how SFCTA has modified and applied SF-CHAMP to answer the questions being asked by planners and decision-makers. The second half will focus on what resources, tools and tricks have aided their success. 25 | 26 | #### Source 27 | 28 | [TMIP](TMIP) 29 | 30 | #### Presenters 31 | 32 | Elizabeth Sall, San Francisco County Transportation Authority 33 | 34 | #### Recorded Date 35 | 36 | 2012-11-15 37 | 38 | ------------------------------------------------------------------------ 39 | 40 | 41 | 42 | -------------------------------------------------------------------------------- /topics/Safety_Analysis.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Safety analysis in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | ## Guidelines 8 | 9 | Safety impacts of a highway project are closely associated with the change in VMT and the crash rate per vehicle mile. In addition, the crash rate may differ across facilities within a project, or the crash rate might vary by alternative. 10 | 11 | ## References 12 | -------------------------------------------------------------------------------- /topics/Scenario_sensitivity_testing_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Scenario/sensitivity testing in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | - Project Level Traffic Forecasting 6 | --- 7 | 8 | Go to the [Project-level traffic forecasting](Project_level_traffic_forecasting) topic page. 9 | 10 | A “[scenario](Scenario_Forecasting_for_Travel_Demand_Modeling)” is comprised of the set of factors that can influence the forecast but are not defined by a project alternative. A scenario might involve the economic, demographic or land-development environment of the project. A “sensitivity” is the amount of change in a single output of a forecast, given a change in a single input to a forecast; formally, a sensitivity is equivalent to an elasticity from the field of economics. Sensitivity testing is useful during model development, but scenario testing is more relevant to the decision process. Scenario testing has the advantage of placing bounds on the range of a forecast and of alerting decision makers about how the forecast might be affected by extraneous factors and assumptions about the future. Scenario testing has the advantage of removing the burden of needing to know future conditions very precisely. 11 | 12 | -------------------------------------------------------------------------------- /topics/Sketch_planning_models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Sketch planning models" 3 | categories: 4 | - Topic Circles 5 | --- 6 | 7 | 8 | 9 | 10 | Summary 11 | ------- 12 | 13 | Sketch planning models or sketch planning tools may be used by planning agencies to address issues that require a quick turn-around time, particularly in situations where the run-time of the primary regional demand forecasting tool is extensive. The models may be limited to only evaluating network impacts due to network changes (holding mode choice outputs constant). 14 | 15 | Sketch planning models are often synonymous with [strategic models](Strategic_Models). Using strategic tools for long range performance-based planning is becoming increasingly valuable as a means to help state and metropolitan area governments select policies and actions to address pressing issues that are fraught with uncertainty. Strategic tools are designed to address a wide range of trends and policies, rather than focusing on details. As a result, many alternative futures and policies can be evaluated, enabling planners to reason more effectively about intended and unintended consequences of prospective policies and test plan resilience to uncertain external influences. Performance metrics set in a strategic phase may be incorporated into subsequent planning, programming and project prioritization processes, as well as monitor plan performance that can in-turn influence long range planning decisions, supportive of long range performance-based planning as outlined in the federal legislation (e.g., Moving Ahead for Progress in the 21st Century (MAP‐21) and FAST). 16 | 17 | ## Appropriate use of sketch planning models and tools 18 | 19 | to be added. 20 | 21 | -------------------------------------------------------------------------------- /topics/Solution_Algorithm.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Solution Algorithm" 3 | categories: 4 | --- 5 | 6 | Summary 7 | ------- 8 | 9 | ------------------------------------------------------------------------ 10 | 11 | -------------------------------------------------------------------------------- /topics/Statewide_Modeling_Case_Studies.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Statewide Modeling Case Studies" 3 | categories: 4 | - Needs Review 5 | - Statewide Models 6 | --- 7 | 8 | This page is part of the Category \[. 9 | 10 | Over 30 states across the U.S. have operational statewide models that are used for policy analysis. Some case studies exemplify how such models are designed and used to support statewide planning. If you know another statewide model really well, please add a short description here. 11 | 12 | [Georgia Statewide Model](Georgia_Statewide_Model) 13 | 14 | [Maryland Statewide Transportation Model (MSTM)](Maryland_Statewide_Transportation_Model) 15 | 16 | -------------------------------------------------------------------------------- /topics/Statewide_Modeling_Subcommittee_ADA10_2_.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Statewide Modeling Subcommittee ADA10(2)" 3 | categories: 4 | - Needs Review 5 | - Statewide Models 6 | --- 7 | 8 | This page is part of the Category \[. 9 | 10 | Statewide Modeling Subcommittee ADA10(2) 11 | The statewide travel forecasting committee has been in existence about 19 years. It is dedicated to statewide and multi-state travel forecasting. It has two parent committees: Statewide Multimodal Transportation Planning and Transportation Demand Forecasting. The committee website is 12 | 13 | Major components of the web site include: 14 | 15 | Presentations from TRB conferences, 16 | source documents and 17 | minutes from subcommittee meetings. 18 | ADA10(2) meets annually at the annual TRB meeting with a focus on current committee activities, research focus area status, state-of-the-practice presentations and the upcoming year’s activities. 19 | 20 | The Statewide Modeling Subcommittee sponsored meetings and workshops have included: 21 | 22 | - TRB Annual Meeting Sessions.; 23 | - Meetings of the TRB Subcommittee on Statewide Travel Forecasting Models; 24 | - Statewide Travel Demand Modeling: Peer Exchange, Transportation Research Circular E-C075, September 2004; 25 | - Statewide planning conference (Atlanta 2009) with statewide modeling workshop; and 26 | - 2013 Planning Applications Conference Workshops. 27 | 28 | 29 | -------------------------------------------------------------------------------- /topics/Stochastic_Traffic_Assignment.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Stochastic Traffic Assignment" 3 | categories: 4 | - Network Assignment 5 | --- 6 | 7 | Summary 8 | ------- 9 | 10 | Stochastic traffic assignment, also known as stochastic user equilibrium assignment, is a variant of the more widely-used deterministic user equilibrium assignment process. It incorporates an error term in the [link capacity function](link_capacity_function) that adds noise to the link travel time estimates in each iteration. This noise represents the imperfect information that travelers have about network conditions. This accounts for uncertainty about travel times that they will encounter in congested conditions, information or perception errors, and as a result of using unfamiliar routes or traveling in new places. It has also been advanced that stochastic variability, if properly characterized, can better represent the inherent day-to-day variability in travel times. The amount of noise added to the calculated link travel times is controlled by a lambda parameter that should be calibrated based on observed or [stated preference survey](stated_preference_survey) data. 11 | 12 | Stochastic traffic assignments have been used primarily in academic research, and are rarely used in practice. [Patriksson (1994)](https://encrypted.google.com/books/about/The_Traffic_Assignment_Problem.html?id=pzVPAAAAMAAJ) covers the topic in much detail. 13 | 14 | ------------------------------------------------------------------------ 15 | 16 | -------------------------------------------------------------------------------- /topics/Synthetic_populations_review_of_the_different_approaches.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Synthetic populations: review of the different approaches" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models 6 | - Papers 7 | - Resources 8 | links: 9 | - type: Paper (PDF) 10 | label: "Link" 11 | url: https://ro.uow.edu.au/cgi/viewcontent.cgi?article=7804&context=eispapers 12 | --- 13 | 14 | 15 | #### Author 16 | 17 | Johan Barthelemy, Eric Cornelis 18 | 19 | #### Source 20 | 21 | CEPS/INSTEAD Working Paper 2012-18 22 | 23 | #### Abstract 24 | 25 | Microsimulations may involve a large number of agents. It is then practically impossible or too expensive to obtain a fully and complete disaggregated data set about these agents of interest. Moreover, if such a dataset was available, its use would be potentially problematic in view of stringent privacy laws. To address this problem one may build an artificial population starting from known aggregate data. Most of the known generation methods are explained in this paper. Their advantages and limitations are discussed and references are given for further details. 26 | 27 | #### Copyright & Usage Permissions 28 | 29 | CEPS/INSTEAD Working Papers are intended to make research findings available and stimulate comments and discussion. They have been approved for circulation but are to be considered preliminary. They have not been edited and have not been subject to any peer review. The views expressed in this paper are those of the author(s) and do not necessarily reflect views of CEPS/INSTEAD. Errors and omissions are the sole responsibility of the author(s). 30 | 31 | #### Publication Date 32 | 33 | 2012 34 | 35 | ------------------------------------------------------------------------ 36 | 37 | 38 | 39 | -------------------------------------------------------------------------------- /topics/TCRP_Report_95_Chapter_12_Transit_Pricing_and_Fares_Traveler_Response_to_Transportation_System_Changes.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "TCRP Report 95: Chapter 12 – Transit Pricing and Fares: Traveler Response to Transportation System Changes" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "TCRP Report 95: Chapter 12 – Transit Pricing and Fares: Traveler Response to Transportation System Changes" 11 | url: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c12.pdf 12 | --- 13 | 14 | "TCRP Report 95: Chapter 12 – Transit Pricing and Fares: Traveler Response to Transportation System Changes" 15 | 16 | #### Author 17 | 18 | Brian E. McCollom, Lead Chapter Author, and Richard H. Pratt, Prinicpal Investigator 19 | 20 | #### Source 21 | 22 | Transportation Research Board Transit Cooperative Research Program 23 | 24 | #### Abstract 25 | 26 | This report chapter addresses transit ridership response to fare changes as applied to conventional urban area bus and rail transit services. Topics covered are: changes in general fare level, changes in fare structure including relationships among fare categories, and free transit. Case studies examine four varied examples of transit pricing changes. 27 | 28 | #### Copyright & Usage Permissions 29 | 30 | Public Domain 31 | 32 | #### Publication Date 33 | 34 | 2004-January-1 35 | 36 | ------------------------------------------------------------------------ 37 | 38 | 39 | 40 | -------------------------------------------------------------------------------- /topics/TCRP_Report_95_Chapter_13_Parking_Pricing_and_Fares_Traveler_Response_to_Transportation_System_Changes.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "TCRP Report 95: Chapter 13 – Parking Pricing and Fares: Traveler Response to Transportation System Changes" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "TCRP Report 95: Chapter 13 – Parking Pricing and Fares: Traveler Response to Transportation System Changes" 11 | url: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c13.pdf 12 | --- 13 | 14 | *Document Title* 15 | 16 | #### Author 17 | 18 | Erin Vaca and J. Richard Kuzmyak, Lead Chapter Authors 19 | 20 | #### Source 21 | 22 | Transportation Research Board Transit Cooperative Research Program 23 | 24 | #### Abstract 25 | 26 | This report chapter presents information on how travelers respond to both the introduction of parking pricing and fees, and to changes in the level, structure, or method of application of parking fees. Included are actions that can change the costs to users of parking even without fee changes, notably through elimination of employer parking subsidies, and fee structures that differentiate by mode of parking (short/long term) or travel (drive-alone/ridesharing). Four comprehensive examples of parking pricing applications are included as case studies. 27 | 28 | #### Copyright & Usage Permissions 29 | 30 | Public Domain 31 | 32 | #### Publication Date 33 | 34 | 2005-January-1 35 | 36 | ------------------------------------------------------------------------ 37 | 38 | 39 | 40 | -------------------------------------------------------------------------------- /topics/TCRP_Synthesis_63.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "TCRP Synthesis 63" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: Report (PDF) 10 | label: "Full Document" 11 | url: http://www.tcrponline.org/PDFDocuments/tsyn63.pdf 12 | --- 13 | 14 | 15 | *Resource Title* 16 | 17 | #### Author 18 | 19 | Bruce Schaller 20 | 21 | #### Source 22 | 23 | #### Abstract 24 | 25 | #### Copyright & Usage Permissions 26 | 27 | #### Publication Date 28 | 29 | 2005-1-1 30 | 31 | ------------------------------------------------------------------------ 32 | 33 | 34 | 35 | -------------------------------------------------------------------------------- /topics/TMIP.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "TMIP" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | The Travel Model Improvement Program (TMIP) was established in 1994 as a partnership of the Federal Highway Administration (FHWA), Federal Transit Administration (FTA), Office of the Secretary of Transportation (OST) and Environmental Protection Agency (EPA) to conduct research as well as deliver technical assistance and training to local, regional and state transportation planning professionals. A critical part of the TMIP program is the transfer of improved modeling, simulation and analysis technology, techniques and practices to transportation planning staff at state and local planning agencies. Recently, TMIP became the Travel Model Improvement Portal(TMIP) and now exists in conjunction with the Freight Model Improvement Portal(FMIP) through a Community of Practice (COP) portal. The [TMIP website](https://tmip.org) and resources have been updated to reflect this TMIP/FMIP collaboration. The objective of this COP is to provide an effective platform to encourage and facilitate information sharing, the exchange of ideas, and capacity building within the travel and freight modeling and planning communities. Peer review panels, webinars and other resources are available via the COP. 8 | 9 | The TFResource and TMIP staff are working closely together to provide complimentary resources to the profession. As both efforts evolve, the collaborations and leveraging of efforts will also evolve. 10 | 11 | 12 | 13 | 14 | 15 | -------------------------------------------------------------------------------- /topics/TMIP_Activity_Based_Model_Webinar_Series_Instructor_Manual.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "TMIP Activity Based Model Webinar Series Instructor Manual" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Activity Based Models 7 | - Papers 8 | - Resources 9 | links: 10 | - type: PDF 11 | label: "Full Document" 12 | url: http://media.tmiponline.org/clearinghouse/ABM_Instructors_Manual/AB_Webinar_Complete.pdf 13 | --- 14 | 15 | *TMIP Activity Based Model Webinar Series Instructor Manual* 16 | 17 | #### Authors 18 | 19 | RSG & PB 20 | 21 | #### Source 22 | 23 | USDOT FHWA FHWA-HEP-13-002 24 | 25 | #### Abstract 26 | 27 | TMIP Activity-Based Modeling Webinar Series Instructor's Manual 28 | 29 | #### Publication Date 30 | 31 | 2012 32 | -------------------------------------------------------------------------------- /topics/T_PICS_Transportation_Project_Impact_Case_Studies.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "T-PICS: Transportation Project Impact Case Studies" 3 | noTOC: true 4 | categories: 5 | - Evaluation And Performance 6 | - Reports 7 | - Resources 8 | - Sketch Planning Models 9 | links: 10 | - type: Website 11 | label: "tpics.us" 12 | url: http://tpics.us/About.aspx 13 | --- 14 | 15 | 16 | #### Author 17 | 18 | Economic Development Research Group (EDRG) 19 | 20 | #### Source 21 | 22 | SHRP2 23 | 24 | #### Abstract 25 | 26 | The Transportation Project Impact System (TPICS) is a product of the US Strategic Highway Research Program (SHRP2), project C03, "Impact of Transportation Capacity on Economic Development and Land Use." The prime contractor was Economic Development Research Group, Inc. (EDR Group). The T-PICS web site was designed by EDR Group and built by ICF Consulting. Case studies of highway project impacts that are included in the TPICS system were prepared by a team of EDR Group, Cambridge Systematics, Wilbur Smith Associates, Texas Transportation Institute and Susan Moses Associates. The project was directed by Stephen Andrle and David Plazak of the Transportation Research Board's SHRP2 Program. 27 | 28 | #### Copyright & Usage Permissions 29 | 30 | T-PICS is an interactive website 31 | 32 | #### Publication Date 33 | 34 | 2011-1-1 35 | 36 | ------------------------------------------------------------------------ 37 | 38 | 39 | 40 | -------------------------------------------------------------------------------- /topics/Temporal_resolution_in_project_level_traffic_forecasting.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Temporal resolution in project-level traffic forecasting" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Guidelines 8 | ========== 9 | 10 | Forecasts may be made for 24-hours, a peak hour, a multihour peak or some other period of time. However, it is important to recognize that delay estimates over a period of time greater than a single hour are not sufficiently trustworthy for project-level work. Therefore, it is essential that a multihour period be modeled by consecutive individual hours. A multihour period may be assembled by combining several one-hour static traffic assignments or by a single dynamic traffic assignment that spans the whole period. Static traffic assignments of less than one hour are unusual. 11 | 12 | References 13 | ========== 14 | 15 | -------------------------------------------------------------------------------- /topics/The_ARC_and_SACOG_Experience_with_Activity_Based_Models_Synthesis_and_Lessons_Learned.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "The ARC and SACOG Experience with Activity-Based Models - Synthesis and Lessons Learned" 3 | noTOC: true 4 | categories: 5 | - Activity Based Models 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "ARC Appendix" 11 | url: http://media.tmiponline.org/clearinghouse/AMPO_report/AMPOPhase2ReportARC_Appendix.pdf 12 | - type: PDF 13 | label: "SACOG Appendix" 14 | url: http://media.tmiponline.org/clearinghouse/AMPO_report/AMPOPhase2ReportSACOG_Appendix.pdf 15 | - type: PDF 16 | label: "Full Document" 17 | url: http://media.tmiponline.org/clearinghouse/AMPO_report/AMPOPhase2MainReportFinal.pdf 18 | --- 19 | 20 | *The ARC and SACOG Experience with Activity-Based Models - Synthesis and Lessons Learned* 21 | 22 | #### Author 23 | 24 | RSG, Inc. 25 | 26 | #### Source 27 | 28 | Association of Metropolitan Planning Organizations 29 | 30 | #### Abstract 31 | 32 | This report represents the second phase of a study commissioned by the Association of Metropolitan Planning Organizations (AMPO) to better understand the experiences of metropolitan planning organizations (MPOs) that have operational activity-based models (ABMs) for use in their planning processes. Specifically, this report synthesizes the experiences of two MPOs: The Atlanta Regional Commission (ARC) and the Sacramento Area Council of Governments (SACOG). 33 | 34 | #### Publication Date 35 | 36 | 2012 37 | 38 | ------------------------------------------------------------------------ 39 | 40 | 41 | 42 | -------------------------------------------------------------------------------- /topics/The_Chicago_Area_Transportation_Study_Creating_the_First_Plan_1955_1962_.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "The Chicago Area Transportation Study: Creating the First Plan (1955-1962)" 3 | noTOC: true 4 | categories: 5 | - Papers 6 | - Resources 7 | - Travel Survey Data 8 | - Trip Based Models 9 | - Urban And Metropolitan Models 10 | links: 11 | - type: Paper (PDF) 12 | label: "Link" 13 | url: http://www.surveyarchive.org/Chicago/cats_1954-62.pdf 14 | --- 15 | 16 | _The Chicago Area Transportation Study: Creating the First Plan (1955-1962)_ 17 | 18 | #### Author 19 | 20 | Andrew V. Plummer 21 | 22 | #### Source 23 | 24 | Author's manuscript 25 | 26 | #### Abstract 27 | 28 | This is a historical account of one of the earliest systematic metropolitan transportation studies in the U.S., the Chicago Area Transportation Study (CATS). This period in CATS' history is widely recognized as establishing both the policy template and technical methods eventually codified as the 3C planning process undertaken by MPOs nationally. Written in a firsthand, non-academic, almost folksy, style by Andy Plummer who retired from CATS in 2000 after about 40 years. 29 | 30 | #### Copyright & Usage Permissions 31 | 32 | None. 33 | 34 | #### Publication Date 35 | 36 | 2010-January-1 37 | -------------------------------------------------------------------------------- /topics/Time_of_Day_Factoring.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Time of Day Factoring" 3 | categories: 4 | --- 5 | 6 | Summary 7 | ------- 8 | 9 | Time of day factoring is a popular, elementary method of estimating the amount of travel occurring within hourly or multihour time periods. Time of day factoring has particular relevance to [Trip-Based Models](https://tfresource.github.io/topics/Trip_based_models.html). Standard time of day factors have been published in NCHRP Report 187, NCHRP Report 365, and NCHRP Report 716. Separate factors are required for each purpose (e.g., HBW, HBO, NHB) and for each direction of travel (production-to-attraction and attraction-to-production) for each hour of interest. Time of day factoring typically converts a 24-hour PA (production-to-attraction) trip table to an OD (origin-destination) trip table for a specific time period. 10 | 11 | ------------------------------------------------------------------------ 12 | 13 | -------------------------------------------------------------------------------- /topics/Tolling_and_Public_Private_Partnerships_in_Texas_Separating_Myth_from_Fact.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Tolling and Public-Private Partnerships in Texas Separating Myth from Fact" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "Tolling and Public-Private Partnerships in Texas Separating Myth from Fact" 11 | url: http://reason.org/files/f4b3060c451c35f004519f3971d05fb3.pdf 12 | --- 13 | 14 | 15 | #### Author 16 | 17 | Robert W. Poole, Jr., Reason Foundation 18 | 19 | #### Source 20 | 21 | Reason Foundation 22 | 23 | #### Abstract 24 | 25 | Texas enacted legislation in 2003 to permit expanded use of tolling and public-private partnerships (PPPs) to increase highway capacity. That law, as strengthened by amendments in 2005, has led to Texas attracting enormous potential private capital investment to expand its highway capacity beyond what would have been considered possible several years ago. The Texas policy has also been cited repeatedly as a model by other states enacting similar enabling legislation since 2003. This report aims to answer some basic questions regarding the PPP experience in Texas: Are long-term PPPs actually sound long-term transportation policy? Could existing public-sector toll agencies raise as much funding for transportation as private toll road companies? Should the state enact a two-year moratorium on CDAs during which time it studies their efficacy? 26 | 27 | #### Copyright & Usage Permissions 28 | 29 | #### Publication Date 30 | 31 | 2007-May-1 32 | 33 | ------------------------------------------------------------------------ 34 | 35 | 36 | 37 | -------------------------------------------------------------------------------- /topics/Topic_Circles.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Topic Circles" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | [Topics](Topic_Circles) are the curated categories used to group content within this wiki. 8 | 9 | Wiki's lack the structured content of information found in most traditional documents featuring a table of contents. Rather, they follow the topical structure of an encyclopedia, where each topic or section – wiki page in this instance – is at the same level as all of the others. Cross-references are used to link similar items together. 10 | 11 | The [committee](https://www.mytrb.org/CommitteeDetails.aspx?CMTID=3709) has adopted the wiki concept of [circles](Topic_Circles) to help organize the review of TF Resource content and identify major topics for targeted attention. The following topics are part of TF Resource at this time. 12 | 13 | Have an idea for a new Topic? Registered contributors can add topic pages or make suggestions for additional content by following the talk button at the top of any page and leaving a comment. 14 | 15 | Thank you for your interest in the Travel Forecasting Resource. 16 | 17 | -------------------------------------------------------------------------------- /topics/Tour_based_models.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Tour-based models" 3 | categories: 4 | - Needs Review 5 | - Activity Based Models 6 | --- 7 | 8 | **Tour-based models** arrange travel into units called tours. Tours are travel events that start at one location and return to that same location. For example, when a person travels to work and returns home, this a home-based work tour. A tour can have two or more trips. 9 | 10 | [Activity-based models](Activity_based_models) are tour-based, but a model does not have to be activity-based to be tour-based. 11 | 12 | Terminology 13 | =========== 14 | 15 | Sub-tours 16 | --------- 17 | 18 | A sub-tour is a tour that occurs temporally within another tour. For example, if a worker goes from home to work, and goes from work to a restaurant back to work, and then goes back home, this activity chain contains one sub-tour. 19 | 20 | Half-tours 21 | ---------- 22 | 23 | Each tour is divided into two **'half-tours**'- one from the primary origin to the primary destination, and one from the primary destination back to the origin. 24 | 25 | Outbound/Inbound 26 | ---------------- 27 | 28 | The half-tour leaving from the primary origin is called **'outbound**. The half-tour leaving from primary destination is called **'inbound**'. 29 | 30 | Intermediate stops 31 | ------------------ 32 | 33 | A tour may have zero or many **'intermediate stops**'. An intermediate stop occurs when a person participates in an activity at a location that is not the tour origin or destination. For example, if a person goes from home to work and picks up coffee along the way, the place where the person got the coffee is an intermediate stop. 34 | 35 | References 36 | ========== 37 | 38 | -------------------------------------------------------------------------------- /topics/Toward_a_dynamic_model_of_individual_activity_pattern_formulation.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Toward a dynamic model of individual activity pattern formulation" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Papers 7 | - Resources 8 | links: 9 | - type: Paper (PDF) 10 | label: "paper" 11 | url: http://krypton.its.uci.edu/its/publications/papers/CASA/UCI-ITS-AS-WP-81-2.pdf 12 | --- 13 | 14 | 15 | *Toward a dynamic model of individual activity pattern formulation* 16 | 17 | #### Author 18 | 19 | Gregory S. Root 20 | 21 | William W. Recker 22 | 23 | #### Source 24 | 25 | University of California Irvine - Institue of Transportation Studies 26 | 27 | #### Abstract 28 | 29 | #### Copyright & Usage Permissions 30 | 31 | Public 32 | 33 | #### Publication Date 34 | 35 | 1981-7-1 36 | 37 | ------------------------------------------------------------------------ 38 | 39 | 40 | 41 | -------------------------------------------------------------------------------- /topics/Transit_Fares.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit Fares" 3 | categories: 4 | - Public Transport (Transit) Modeling 5 | - Transportation Networks 6 | --- 7 | 8 | Transit Fares can be represented in numerous ways and are highly-dependent upon the commercial modeling system that is used. Fares can be represented as a flat fare, transfer discounts, Some systems can accurately represent all transfer combinations while others this has to be approximated. 9 | 10 | Fare discounts and approximations 11 | --------------------------------- 12 | 13 | Sometimes when certain fare discounts are very prevalent, a modeler may choose to represent the average fare paid as the modeled fare. This can be approximated by dividing the total fare revenue for an agency by the total ridership. Other common approximations are to use a high-value ticket discount price, or the price of a monthly pass divided by a common number of trips. 14 | 15 | Fare Pass Model 16 | --------------- 17 | 18 | In some models, there is a separate step to forecast which individuals decide to buy transit passes. Individuals with passes would then have a zero marginal cost to riding transit. 19 | 20 | Ultimately, it is up to the modeler to decide what an appropriate level of approximation is for the purposes of the transit system that is being modeled and the effect that it will have on the project that the model is being used for. 21 | 22 | ------------------------------------------------------------------------ 23 | 24 | -------------------------------------------------------------------------------- /topics/Transit_Network_Assignment.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit Network Assignment" 3 | categories: 4 | - Network Assignment 5 | - Public Transport (Transit) Modeling 6 | - Transportation Networks 7 | - Urban And Metropolitan Models 8 | --- 9 | 10 | Transit network assignment is the process of determining the routes taken by the transit demand from the mode choice model. The same networks, parameters, and methods should be used for transit assignment that were used for determining the [transit network service levels](Transit_Network_Service_Determination). In fact, in many packages there is just one more key word in the script that separates the two processes (i.e. ASSIGN=TRUE, TRIPS=MatrixName) 11 | 12 | For a base year, the output of transit assignment can be compared with observed [transit data](Transit_Data) through a process called [validation](Model_Calibration_and_Validation#Trip_Assignment_Models). 13 | 14 | -------------------------------------------------------------------------------- /topics/Transit_Route.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit Route" 3 | categories: 4 | - Needs Review 5 | - Public Transport (Transit) Modeling 6 | - Transportation Networks 7 | --- 8 | 9 | Transit routes represent how [Transit Vehicles](Transit_Vehicles) traverse the network. Transit route characteristics include: 10 | 11 | 1. Route name: Often separated by direction (i.e. Inbound or Outbound or similar). One example would be MUNI\_30X\_IN to represent the SFMTA Muni Route, 30-Express, in the inbound direction. 12 | 2. Directions: where the vehicle drives, represented by a list of nodes or links 13 | 3. Stopping Pattern: Often embedded in the directions, are notes about what nodes constitute transit stops. In many systems, transit stops can be restricted to only allow alightings, or only allow boardings. 14 | 4. [Transit Vehicles](Transit_Vehicles) type 15 | 5. [Transit Route Frequency](Transit_Route_Frequency), which is often designated by time period can be represented by a schedule or by an average headway 16 | 17 | Some other common attributes of transit routes include: 18 | 19 | 1. special instructions about how travel time is calculated, including the delays associated with making a stop 20 | 2. transit agency, which can be used to help determine fares 21 | 22 | ------------------------------------------------------------------------ 23 | 24 | -------------------------------------------------------------------------------- /topics/Transit_Route_Frequency.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit Route Frequency" 3 | categories: 4 | - Public Transport (Transit) Modeling 5 | --- 6 | 7 | [Transit Route](Transit_Route) frequency can be represented in a variety of ways. The two most common ways are: 8 | 9 | 1. Schedule-based 10 | 2. Headway-based 11 | 12 | ------------------------------------------------------------------------ 13 | 14 | -------------------------------------------------------------------------------- /topics/Transit_Vehicles.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit Vehicles" 3 | categories: 4 | - Needs Review 5 | - Public Transport (Transit) Modeling 6 | --- 7 | 8 | Some characteristics of transit vehicles within [Public Transport Modeling](Public_transport_transit_modeling) include: 9 | 10 | - Seated and crush-level capacities - required for a system that accounts for crowding 11 | - Acceleration, deceleration, and maximum speeds - required if you want to translate to a traffic simulation and do an operational analysis 12 | - Power source, (i.e. electric, diesel, diesel hybrid) - useful for doing a GHG analysis 13 | - Number of doors - useful for being able to calculate dwell times as a function of passenger boarding/alighting 14 | 15 | ------------------------------------------------------------------------ 16 | 17 | -------------------------------------------------------------------------------- /topics/Transit_crowding.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit crowding" 3 | categories: 4 | --- 5 | 6 | Transit crowding is an important consideration in urban areas where the core transit network cannot accommodate demand. There are several ways that transit crowding has been addressed: 7 | 8 | 1. Modifying the perceived in-vehicle time to account for the discomfort of being crowded and/or not getting a seat 9 | 2. Modifying the wait time for transit to essentially shadow-price crowded lines (this can be done in many commercial transit route packages) 10 | 3. A modification to the above with a binary iterative process as opposed to a continuous-iterative process ([as done at SFCTA](SFCTA_Paper_incorporating_crowding)) 11 | 4. Manual reassignment of overcrowded transit riders after the completion of the travel model 12 | 13 | ------------------------------------------------------------------------ 14 | 15 | -------------------------------------------------------------------------------- /topics/Transit_dwell_time.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transit dwell time" 3 | categories: 4 | --- 5 | 6 | Dwell time can be a significant component of the overall travel time for transit. In San Francisco, about half of the bus travel time is taken up by the servicing of passengers or by the bus either pulling in or out of a stop. 7 | 8 | Dwell time to service passengers is often represented in one of three ways: 9 | 10 | 1. Not explicitly included: this is an appropriate simplification when the dwell time is either not of much consequence to the total travel time (i.e. an express or low-ridership route), or if it is predictable and already included in the in-vehicle travel time (this is common for rail) 11 | 2. Included as a constant value: this is an appropriate simplification if the dwell time is fairly even throughout the route and ridership is evenly distributed. 12 | 3. Calculated as a constant value (pull-out/pull-in time) plus a function of boardings and alightings and other variables that may affect dwell time such as crowding levels. 13 | 14 | Based on [research at SFCTA](SFCTA_Paper_incorporating_crowding), it may be appropriate to segment the above techniques and parameters by mode, vehicle and route type (i.e. an urban articulated bus will have different boarding and alighting times than a van or one-door vehicle) 15 | 16 | One also may want to consider the application of policies such as bus bulbs, all-door boarding, and low-floor vehicles to the dwell time. 17 | 18 | ------------------------------------------------------------------------ 19 | 20 | -------------------------------------------------------------------------------- /topics/Transportation_Elasticities_How_Prices_and_Other_Factors_Affect_Travel_Behavior.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Transportation Elasticities: How Prices and Other Factors Affect Travel Behavior" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: Report (PDF) 10 | label: "Report" 11 | url: http://www.vtpi.org/elasticities.pdf 12 | --- 13 | 14 | 15 | *Resource Title* 16 | 17 | #### Author 18 | 19 | Todd Litman 20 | 21 | #### Source 22 | 23 | Victoria Transport Policy Institute 24 | 25 | #### Abstract 26 | 27 | This report investigates the influence that prices have on travel behavior. It summarizes research on various types of transportation elasticities and describes how to use this information to predict the travel impacts of specific TDM strategies. 28 | 29 | #### Copyright & Usage Permissions 30 | 31 | Todd Alexander Litman © 2005-2013 32 | You are welcome and encouraged to copy, distribute, share and excerpt this document and its ideas, provided the 33 | author is given attribution. Please send your corrections, comments and suggestions for improving it. 34 | 35 | #### Publication Date 36 | 37 | 2013-March-12 38 | 39 | ------------------------------------------------------------------------ 40 | 41 | 42 | 43 | -------------------------------------------------------------------------------- /topics/Travel_Behavior_of_Diverse_Populations.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Travel Behavior of Diverse Populations" 3 | categories: 4 | - Travel Behavior 5 | --- 6 | 7 | ### Elderly 8 | 9 | ### Women 10 | 11 | The literature has established that women in the U.S. tend to have more frequent, shorter trips than men. Women also tend to use transit more often than men.[^1] 12 | 13 | Research by Susan Hanson found that, “Women with no children at home averaged a slightly longer commuting time than women with children, but still not as long on average as men. . The presence or absence of children had no effect on men's commuting time." [^2] 14 | 15 | ### Minorities 16 | 17 | 18 | 19 | ### Children 20 | 21 | ### Immigrants 22 | 23 | ------------------------------------------------------------------------ 24 | 25 | 26 | 27 | ------------------------------------------------------------------------ 28 | 29 | [^1]: Taylor, Brian D. and Mauch, Michael. by Womens Travel Issues: Proceedings from the Second National Conference, October 1996, FHWA-PL-97-024, Office of Highway Information Management, HPM-40, Federal Highway Administration. Washington, DC: U.S. Department of Transportation. 1998 Pages 371-405. 30 | 31 | [^2]: Hanson, Susan. “Women’s Place. Professor Susan Hanson’s research. Accessed April 2008: 32 | 33 | -------------------------------------------------------------------------------- /topics/Travel_Behaviour_A_review_of_recent_literature.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Travel Behaviour: A review of recent literature" 3 | noTOC: true 4 | categories: 5 | - Reports 6 | - Resources 7 | links: 8 | - type: PDF 9 | label: "Report" 10 | url: https://urbanet.curtin.edu.au/wp-content/uploads/sites/40/2018/12/ARC_TOD_Working_Paper_3.pdf 11 | --- 12 | 13 | 14 | *Travel Behaviour: A review of recent literature: IMPACTS OF TRANSIT LED DEVELOPMENT IN A NEW RAIL CORRIDOR WORKING PAPER No. 3* 15 | 16 | #### Author 17 | 18 | - Carey Curtis 19 | - Tim Perkins 20 | 21 | #### Source 22 | 23 | Department of Urban and Regional Planning, Curtin University 24 | 25 | #### Abstract 26 | 27 | This paper presents a review of literature in the travel behavior analysis field from the period of approximately 2001-2006. The authors were focusing on the analysis of factors which influenced travel behavior in order to analyze the impact of transit oriented developments on travel. The review focused primarily on work deriving from the design and analysis of household travel surveys and on determining travel behavior sensitivities from them, while also reviewing work presenting conceptual models of travel behavior and other reviews of previous work. Overall 96 papers were reviewed. 28 | 29 | #### Copyright & Usage Permissions 30 | 31 | Copyrighted, available at website. 32 | 33 | #### Publication Date 34 | 35 | 2006 36 | -------------------------------------------------------------------------------- /topics/Travel_Forecasting_Results_Report.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Travel Forecasting Results Report" 3 | categories: 4 | --- 5 | 6 | FTA requires documentation of the travel forecasts for projects applying for Section 5309 [New Starts funding](https://www.transit.dot.gov/CIG). This documentation is focused on the forecasts, not the forecasting methods. It consists of a succinct narrative of the benefits of the project and the impacted travel markets, as well as a series of summary tabulations. 7 | 8 | The summary tabulations provide the supporting information for the narrative. They include disaggregate district-to-district tables of project trips, auto VMT, systemwide transit trips, socio-economic data, and highway speeds. The summary tabulations can be produced using any travel demand software, Excel, FTA's Summit program, or a combination of software. 9 | 10 | The documentation gets updated over time. As an example, the documentation updated in July 2019 is located in the [Reporting Instructions](http://www.transit.dot.gov/sites/fta.dot.gov/files/docs/funding/grant-programs/capital-investments/8886/fy-21-ss-reporting-instructions-final.doc). 11 | 12 | ------------------------------------------------------------------------ 13 | 14 | -------------------------------------------------------------------------------- /topics/Travel_survey_data.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Travel survey data" 3 | categories: 4 | 5 | --- 6 | 7 | 1. REDIRECT [Travel surveys](Travel_surveys) 8 | 9 | 10 | -------------------------------------------------------------------------------- /topics/Trip_Generation.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Trip Generation" 3 | categories: 4 | - Needs Review 5 | --- 6 | 7 | Summary 8 | ------- 9 | 10 | Trip generation is traditionally the first step in 4-step travel models. Trip generation estimates for an individual [traffic analysis zone](Traffic_Analysis_Zones) (TAZs) the number of trip ends produced or attracted by that zone. Trip ends produced are called "trip productions", and trip ends attracted are called "trip attractions". A trip is produced where the need (or desire) for travel is located; and a trip is attracted where the need (or desire) is satisfied. A trip production can be either an origin or a destination, and a trip attraction can be either an origin or a destination. Productions and attractions are separately tabulated for each trip purpose (e.g., HBW, HBO, NHB). 11 | 12 | One of the more popular methods of trip production calculation is cross-classification. Cross-classification is described in NCHRP Report 716, among many sources. A popular method of trip attraction calculation is by linear equations. Neither of these two methods use measures of mobility or [accessibility](Accessibility). Inputs consists entirely of forecasted socioeconomic or demographic characteristics of zones. 13 | 14 | A subsequent step, [trip distribution](Spatial_Interaction_Models), very often requires that the total of all productions equal the total of all attractions for each trip purpose. Consequently, an important part of trip generation is "balancing", where inconsistencies between productions and attractions are reconciled. Consistency can be achieved by holding productions constant and varying attractions or vice versa. 15 | 16 | ------------------------------------------------------------------------ 17 | -------------------------------------------------------------------------------- /topics/Trip_interchange.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Trip interchange" 3 | categories: 4 | - Needs Review 5 | - Trip Based Models 6 | --- 7 | 8 | Summary 9 | ------- 10 | 11 | A trip is a one-way journey between an origin and a destination. Origins and destinations are “trip ends”. In trip-based models, locations of trip ends are aggregated into [traffic analysis zones](Traffic_Analysis_Zones) (TAZs). A traffic analysis zone is usually represented on networks by a type of node called a “centroid”. A trip is distinguished from a “tour”, which is comprised of two or more trips, with the tour starting and ending at the same location. A trip interchange is an origin-destination pair. One of the properties of an origin-destination pair is the number of trips between them over a given period of time. 12 | 13 | ------------------------------------------------------------------------ 14 | 15 | -------------------------------------------------------------------------------- /topics/Twin_Cities_HOV_Study_Final_Report.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Twin Cities HOV Study - Final Report" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - Reports 7 | - Resources 8 | links: 9 | - type: PDF 10 | label: "Full Document" 11 | url: http://www.dot.state.mn.us/information/hov/report.html 12 | --- 13 | 14 | *Twin Cities HOV Study - Final Report* 15 | 16 | #### Author 17 | 18 | Cambridge Systematics, Inc. 19 | 20 | #### Source 21 | 22 | Minnesota DOT 23 | 24 | #### Abstract 25 | 26 | This study uses travel demand modeling and market research methodologies to evaluate the potential traffic flow, safety and economic impacts of opening the HOV lanes on both I-394 and I-35W without changing actual lane operation. As a secondary research, it also reviews current trends in HOV deployment across the country and to compare these trends with the operation of HOV lanes in the Twin Cities. The study was in response to Bill H.F 1054 requested that “Mn/DOT conduct a study of how opening the High-Occupancy Vehicle (HOV) lanes on I-394 to general-purpose traffic would impact traffic flow and safety.” 27 | 28 | #### Publication Date 29 | 30 | 2002-2-1 31 | 32 | ------------------------------------------------------------------------ 33 | 34 | 35 | 36 | -------------------------------------------------------------------------------- /topics/Using_policy_to_affect_travel_behavior.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Using policy to affect travel behavior" 3 | categories: 4 | --- 5 | 6 | ### Travel Behavior and the Built Environment 7 | 8 | Travel demand has been found to be generally inelastic with respect to built environment variables. [^1] 9 | 10 | ------------------------------------------------------------------------ 11 | 12 | 13 | 14 | ------------------------------------------------------------------------ 15 | 16 | [^1]: Ewing, Reid, and Robert Cervero. "Travel and the Built Environment. A Meta-Analysis." Journal of the American Planning Association. 76.3 (2010): pp. 265-294. Print 17 | 18 | -------------------------------------------------------------------------------- /topics/Utility.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Utility" 3 | categories: 4 | --- 5 | 6 | Utility is a mathematical description of how favorable an option is, relative to other options. Utilities are unit-less, and sometimes expressed as values between 0 (no utility) and 1 (highest utility). Sometimes, utilities are expressed as negative numbers to represent the burden of an action. For example, the utility for taking the bus can be more negative than the utility for taking a car in a mode choice model to express the potential added burden of waiting for the bus, transferring, and longer travel times on the bus, as applicable to the specific conditions. 7 | 8 | Further reading available on [Wikipedia](http://en.wikipedia.org/wiki/Utility). 9 | -------------------------------------------------------------------------------- /topics/Washington_State_Comprehensive_Tolling_Study_Volume_1_Final_Report.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Washington State Comprehensive Tolling Study Volume 1 Final Report" 3 | noTOC: true 4 | categories: 5 | - Needs Review 6 | - High Occupancy Vehicle Lanes 7 | - Pricing Sudies 8 | - Reports 9 | - Resources 10 | - Toll Facilities And Managed Lanes 11 | links: 12 | - type: PDF 13 | label: "Full Document" 14 | url: http://www.camsys.com/pubs/WS_TollStudy_FinalReport_V1.pdf 15 | --- 16 | 17 | *Washington State Comprehensive Tolling Study Volume 1 Final Report* 18 | 19 | #### Author 20 | 21 | Cambridge Systematics, Inc. 22 | 23 | #### Source 24 | 25 | Washington State Transportation Commission 26 | 27 | #### Abstract 28 | 29 | The study is to help Washington State make policy-level decisions on if, where, when and how to toll by providing a practical step-by-step tolling strategy for the State. Eight policy questions were asked and investigated in the report. The answers were used to test some of the key ideas as well as to elect the illustrative examples of potential toll projects. A set of recommended policies were proposed intended to guide Washington as it develops toll facilities in the State. Legal issues that might be involved in implementing the policies were also analyzed. 30 | 31 | #### Publication Date 32 | 33 | 2006-9-1 34 | 35 | ------------------------------------------------------------------------ 36 | 37 | 38 | 39 | -------------------------------------------------------------------------------- /topics/Webinars_and_Videos.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Webinars and Videos" 3 | categories: 4 | - Needs Review 5 | - Resources 6 | --- 7 | 8 | 9 | 10 | -------------------------------------------------------------------------------- /topics/glossary.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Glossary' 3 | --- 4 | 5 | Terms and acronyms used in the travel forecasting profession. 6 | 7 | --- 8 | 9 |
10 | 11 | 12 | -------------------------------------------------------------------------------- /vscode-tfresource.code-workspace: -------------------------------------------------------------------------------- 1 | { 2 | "folders": [ 3 | { 4 | "path": "." 5 | } 6 | ], 7 | "settings": {} 8 | } --------------------------------------------------------------------------------