├── .github ├── PULL_REQUEST_TEMPLATE.md └── ISSUE_TEMPLATE.md ├── CONTRIBUTING.md ├── protos └── causal_labels.proto ├── README.md └── LICENSE /.github/PULL_REQUEST_TEMPLATE.md: -------------------------------------------------------------------------------- 1 | Fixes # 2 | 3 | > It's a good idea to open an issue first for discussion. 4 | 5 | - [ ] Tests pass 6 | - [ ] Appropriate changes to README are included in PR -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE.md: -------------------------------------------------------------------------------- 1 | ## Expected Behavior 2 | 3 | 4 | ## Actual Behavior 5 | 6 | 7 | ## Steps to Reproduce the Problem 8 | 9 | 1. 10 | 1. 11 | 1. 12 | 13 | ## Specifications 14 | 15 | - Version: 16 | - Platform: -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # How to Contribute 2 | 3 | We'd love to accept your patches and contributions to this project. There are 4 | just a few small guidelines you need to follow. 5 | 6 | ## Contributor License Agreement 7 | 8 | Contributions to this project must be accompanied by a Contributor License 9 | Agreement. You (or your employer) retain the copyright to your contribution; 10 | this simply gives us permission to use and redistribute your contributions as 11 | part of the project. Head over to to see 12 | your current agreements on file or to sign a new one. 13 | 14 | You generally only need to submit a CLA once, so if you've already submitted one 15 | (even if it was for a different project), you probably don't need to do it 16 | again. 17 | 18 | ## Code Reviews 19 | 20 | All submissions, including submissions by project members, require review. We 21 | use GitHub pull requests for this purpose. Consult 22 | [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more 23 | information on using pull requests. 24 | 25 | ## Community Guidelines 26 | 27 | This project follows [Google's Open Source Community 28 | Guidelines](https://opensource.google/conduct/). 29 | -------------------------------------------------------------------------------- /protos/causal_labels.proto: -------------------------------------------------------------------------------- 1 | /*Copyright 2022 Google LLC 2 | 3 | Licensed under the Apache License, Version 2.0 (the "License"); 4 | you may not use this file except in compliance with the License. 5 | You may obtain a copy of the License at 6 | 7 | https://www.apache.org/licenses/LICENSE-2.0 8 | 9 | Unless required by applicable law or agreed to in writing, software 10 | distributed under the License is distributed on an "AS IS" BASIS, 11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | See the License for the specific language governing permissions and 13 | limitations under the License. 14 | ==========================================================================*/ 15 | 16 | // This proto defines the causal labels. 17 | syntax = "proto2"; 18 | 19 | package waymo.causal_agents; 20 | 21 | message CausalLabels { 22 | // The unique ID for the scenario. 23 | optional string scenario_id = 2; 24 | 25 | // A list of results from individual labelers 26 | repeated LabelerResults labeler_results = 1; 27 | } 28 | 29 | message LabelerResults { 30 | // A list of causal agent ids identified by the labeler. A causal agent is 31 | // an agent whose modification causes the ground truth trajectory of 32 | // the AV to change. 33 | repeated string causal_agent_ids = 1; 34 | } 35 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships 2 | 3 | The causal agent labels are an additional attribute to the 4 | [Waymo Open Motion Dataset](https://waymo.com/open/data/motion). 5 | In addition to causal agent labels, we also release perturbed copies of the 6 | Waymo Open Motion Dataset validation dataset, which serve as robustness 7 | benchmarks to aid the research community in building more reliable and safe 8 | models for motion forecasting. For more information, please see the paper 9 | [CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal 10 | Relationships](https://arxiv.org/abs/2207.03586). 11 | 12 | ## Accessing the Data 13 | 14 | In order to access the data, please go to 15 | [https://www.waymo.com/open](https://www.waymo.com/open) and click on Access 16 | Waymo Open Dataset, which requires a user to sign in with Google and accept the 17 | Waymo Open Dataset license terms. After logging in, please visit 18 | [https://console.cloud.google.com/storage/browser/waymo_open_dataset_causal_agents](https://console.cloud.google.com/storage/browser/waymo_open_dataset_causal_agents) 19 | to download the labels. 20 | 21 | ## Dataset format 22 | 23 | ### Causal Agent Labels 24 | 25 | The causal agent labels are released as a TFRecord of causal labels protos 26 | ([causal_label.proto](https://github.com/google-research/causal-agents/blob/main/protos/causal_labels.proto)). 27 | 28 | The protocol buffer format for causal labels includes the following fields: 29 | 30 | **CausalLabels** 31 | 32 | - scenario_id: The unique string identifier for the scenario. 33 | - labeler_results: A list of LabelerResults, one from each individual who 34 | labeled the datasets. Each scenario should have at least 5 individual 35 | labelers. 36 | 37 | **LabelerResults** 38 | 39 | - causal_agent_ids: A list of causal agent id strings entered by the labeler 40 | in the submission box. The agent ids should correspond to the 41 | ["id" field](https://github.com/waymo-research/waymo-open-dataset/blob/master/waymo_open_dataset/protos/scenario.proto#L62) 42 | for the object Track in the Scenario proto. Note that the agent ids may be 43 | repeated in the list (they are not necessarily unique), and in a small 44 | number of cases the labeler may have entered a string that cannot be parsed 45 | as an agent id. 46 | 47 | ### Perturbed Datasets 48 | 49 | We release four perturbed datasets: 50 | 51 | 1. **RemoveNoncausal** 52 | - Removes all non-causal agents in the dataset. 53 | 2. **RemoveNoncausalEqual** 54 | - Removes an equal number of randomly selected non-causal agents as there 55 | are causal agents in the scene. RemoveNoncausalEqual is meant to be a 56 | less aggressive form of RemoveNoncausal since it deletes fewer agents 57 | and it allows us to compare to RemoveCausal when controlling for the 58 | number of agents deleted. 59 | 3. **RemoveStatic** 60 | - Removes agents whose xyz positions do not change above a certain 61 | threshold (e.g. parked cars). Not all static agents are non-causal. 62 | 4. **RemoveCausal** 63 | - Removes all causal agents in the dataset, i.e., the complement of 64 | RemoveNoncausal. 65 | 66 | Among them, we categorize both RemoveNoncausal and RemoveNoncausalEqual as 67 | “non-causal” perturbations and we recommend these datasets as benchmarks for 68 | measuring robustness in future work. 69 | 70 | We include RemoveStatic and RemoveCausal as baselines. In our own work, we used 71 | these datasets to sanity check model behavior (e.g. we expect the model to be 72 | more sensitive to removing causal agents than non-causal or static agents). 73 | 74 | To delete an agent from the original dataset, we set the 75 | [valid bit](https://github.com/waymo-research/waymo-open-dataset/blob/master/waymo_open_dataset/protos/scenario.proto#L47) 76 | of the corresponding agent to False for all time steps. Please double check that 77 | any model you evaluate on the perturbed datasets correctly ignores all agent 78 | state if the valid bit is false. (We verified this for all models we evaluated 79 | in the paper). 80 | 81 | We provide each perturbed dataset as sharded 82 | [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) files 83 | containing 84 | [WOMD tf.Example protos](https://waymo.com/open/data/motion/tfexample). 85 | 86 | ## License 87 | 88 | This code repository is licensed under the Apache License, Version 2.0. 89 | 90 | ## Citation 91 | 92 | If you use this data, please include the following citation: 93 | 94 | > @article{roelofs2022causalagents, title={CausalAgents: A Robustness Benchmark 95 | > for Motion Forecasting using Causal Relationships}, author={Roelofs, Rebecca 96 | > and Sun, Liting and Caine, Ben and Refaat, Khaled S and Sapp, Ben and 97 | > Ettinger, Scott and Chai, Wei}, journal={arXiv preprint arXiv:2207.03586}, 98 | > year={2022} } 99 | 100 | ## Disclaimer 101 | 102 | This is not an officially supported Google product. 103 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | 2 | Apache License 3 | Version 2.0, January 2004 4 | http://www.apache.org/licenses/ 5 | 6 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 7 | 8 | 1. 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