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README.md
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license: apache-2.0
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---
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license: apache-2.0
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---
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# ACT-Bench
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`ACT-Bench` is a dedicated framework for quantitatively evaluating the action controllability of world models for autonomous driving.
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It focuses on measuring how well a world model can generate driving scenes conditioned on specified trajectories.
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<img src="https://github.com/turingmotors/ACT-Bench/blob/main/assets/overview.png" alt="Overview of the Dataset" width="600">
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For more details, please refer our [paper]() and [repository](https://github.com/turingmotors/ACT-Bench).
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## Data fields
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| **Key** | **Value** |
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|-------------------------------|------------------------------------------------------------------|
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| **sample_id** | 0 |
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| **label** | 'straight_constant_speed/straight_constant_speed_10kmph' |
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| **context_frames** | ['sweeps/CAM_FRONT/n015-2018-08-02-17-16-37+0800__CAM_FRONT__1533201487512460.jpg','sweeps/CAM_FRONT/n015-2018-08-02-17-16-37+0800__CAM_FRONT__1533201487612460.jpg','samples/CAM_FRONT/n015-2018-08-02-17-16-37+0800__CAM_FRONT__1533201487762460.jpg'] |
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| **instruction_trajs** | [[[0.0, 0.0, 0.0], [0.1545938742, 0.0015977411, -0.0206596931], [0.3063817081, 0.0019410192, -0.0114837886], [0.4497439065, 0.0027015515, -0.027025583], [0.6050902104, 0.002897561, -0.0230843033], [0.7498937661, 0.0028746845, -0.0432883387], [0.8932801666, 0.0027740429, -0.0449931452], [1.0461783792, 0.0027341864, -0.0609023298], [1.1934560378, 0.0026207325, -0.0626793795], [1.3314688069, 0.002331042, -0.083836065], [1.4882952761, 0.0021888225, -0.0833974201], [1.6343445922, 0.0021784357, -0.1030258874], [1.7774288686, 0.0019280693, -0.0995250479], [1.9282369453, 0.0017355272, -0.1257697433], [2.0736730734, 0.0013283469, -0.1290765928], [2.2130084402, 0.0011821295, -0.1515462308], [2.3587170349, 0.0011464657, -0.1489038888], [2.5127366379, 0.0010401979, -0.1685882206], [2.652663411, 0.0008351443, -0.1706014231], [2.8040034852, 0.0005308638, -0.1906429445], [2.9546874643, 0.0003028058, -0.1814105658], [3.098129893, 0.0001099507, -0.1986876182], [3.2477339776, -9.86779e-05, -0.1938415363], [3.3913945285, -0.0004952867, -0.2175208151], [3.5375306412, -0.0010135945, -0.2182340147], [3.6820731288, -0.001606249, -0.2416164848], [3.8279886236, -0.0021923962, -0.2411775227], [3.969924299, -0.0025448799, -0.2629197723], [4.1173996536, -0.0032625234, -0.263342105], [4.2608852146, -0.00372057, -0.2862758575], [4.3976864233, -0.0043610743, -0.2868744325], [4.5461465324, -0.0048756002, -0.3147401786], [4.6937375295, -0.0055456191, -0.3118187509], [4.8355738212, -0.0058713778, -0.3335816396], [4.9815369191, -0.0058726867, -0.3481201454], [5.1292536114, -0.0065586828, -0.343004249], [5.2652689873, -0.0072471006, -0.3474833218], [5.4155127607, -0.0074426697, -0.3684240186], [5.5638769338, -0.0081954509, -0.3638649342], [5.707405646, -0.0085145329, -0.37765957], [5.8565373943, -0.0093398237, -0.3754173488], [5.9987280205, -0.0099226852, -0.4002108294], [6.1446056388, -0.0107350954, -0.4018748844], [6.2867674027, -0.0115938312, -0.4275775659], [6.4344388492, -0.0125163437, -0.4219962191], [6.576710747, -0.0136388196, -0.4450902563], [6.716435109, -0.0145731886, -0.4416513665], [6.868338088, -0.0157876493, -0.4588417966], [7.0145481629, -0.0169398894, -0.4566243329], [7.1504452338, -0.0183231311, -0.4806745948], [7.3029298241, -0.0194984322, -0.4857886661], [7.4431224522, -0.0208558857, -0.5107711508], [7.5846788069, -0.0219164955, -0.5117771397], [7.7352918213, -0.0229614355, -0.5298967143], [7.8822503429, -0.0238655488, -0.5281344161], [8.0203600833, -0.0247095883, -0.5483177376], [8.1746536442, -0.0259923694, -0.5476485202], [8.3163978205, -0.0268716349, -0.5702512244], [8.4553645875, -0.0278297602, -0.5790391197], [8.5969749414, -0.0289897489, -0.6055032887]], ... |
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| **reference_traj** | [[0.0, 0.0, 0.0], [0.3063817081, 0.0019410192, -0.0114837886], [0.6050902104, 0.002897561, -0.0230843033], [0.8932801666, 0.0027740429, -0.0449931452], [1.1934560378, 0.0026207325, -0.0626793795], [1.4882952761, 0.0021888225, -0.0833974201], [1.7774288686, 0.0019280693, -0.0995250479], [2.0736730734, 0.0013283469, -0.1290765928], [2.3587170349, 0.0011464657, -0.1489038888], [2.652663411, 0.0008351443, -0.1706014231], [2.9546874643, 0.0003028058, -0.1814105658], [3.2477339776, -9.86779e-05, -0.1938415363], [3.5375306412, -0.0010135945, -0.2182340147], [3.8279886236, -0.0021923962, -0.2411775227], [4.1173996536, -0.0032625234, -0.263342105], [4.3976864233, -0.0043610743, -0.2868744325], [4.6937375295, -0.0055456191, -0.3118187509], [4.9815369191, -0.0058726867, -0.3481201454], [5.2652689873, -0.0072471006, -0.3474833218], [5.5638769338, -0.0081954509, -0.3638649342], [5.8565373943, -0.0093398237, -0.3754173488], [6.1446056388, -0.0107350954, -0.4018748844], [6.4344388492, -0.0125163437, -0.4219962191], [6.716435109, -0.0145731886, -0.4416513665], [7.0145481629, -0.0169398894, -0.4566243329], [7.3029298241, -0.0194984322, -0.4857886661], [7.5846788069, -0.0219164955, -0.5117771397], [7.8822503429, -0.0238655488, -0.5281344161], [8.1746536442, -0.0259923694, -0.5476485202], [8.4553645875, -0.0278297602, -0.5790391197], [8.7460786149, -0.0302324411, -0.6148562878], [9.040228578, -0.0320762238, -0.6391508753], [9.3238627154, -0.0334427094, -0.6567384988], [9.6242967538, -0.0349175272, -0.675390711], [9.9159747274, -0.0361669985, -0.7020474284], [10.2029848123, -0.0383206259, -0.7409547588], [10.485217797, -0.0402655886, -0.7784671144], [10.7852857398, -0.0415422365, -0.808403356], [11.0714450976, -0.0426406971, -0.8327939143], [11.3716683909, -0.0438444619, -0.8601736098], [11.6663477515, -0.044536854, -0.8800681964], [11.9537060995, -0.0457889104, -0.9064147281], [12.2546047035, -0.046582522, -0.932251343], [12.5430745076, -0.046996187, -0.961586981], [12.8331523584, -0.0482537294, -0.9948334053], [13.1342964502, -0.0489972987, -1.0360002826], [13.4312132278, -0.0493575167, -1.0671797101], [13.7167782768, -0.0493845646, -1.0965326758], [14.0242449794, -0.0484199283, -1.122908192], [14.3217588305, -0.0482550798, -1.1533763216]] |
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| **intrinsic** | [[1266.4172030466, 0.0, 816.2670197448],[0.0, 1266.4172030466, 491.5070657929],[0.0, 0.0, 1.0]] |
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### Labels
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The `label` field is a string that represents one of the following high-level driving actions:
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```python
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[
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'curving_to_left/curving_to_left_moderate',
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'curving_to_left/curving_to_left_sharp',
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'curving_to_left/curving_to_left_wide',
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'curving_to_right/curving_to_right_moderate',
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'curving_to_right/curving_to_right_sharp',
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'curving_to_right/curving_to_right_wide',
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'shifting_towards_left/shifting_towards_left_short',
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'shifting_towards_right/shifting_towards_right_long',
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'shifting_towards_right/shifting_towards_right_short',
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'starting/starting_20kmph',
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'starting/starting_25kmph',
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'starting/starting_30kmph',
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'stopping/stopping_15kmph',
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'stopping/stopping_20kmph',
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'stopping/stopping_25kmph',
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'stopping/stopping_30kmph',
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'stopping/stopping_35kmph',
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'stopping/stopping_40kmph',
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'stopping/stopping_45kmph',
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'straight_accelerating/straight_accelerating_15kmph',
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'straight_accelerating/straight_accelerating_20kmph',
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'straight_accelerating/straight_accelerating_25kmph',
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'straight_constant_speed/straight_constant_speed_10kmph',
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'straight_constant_speed/straight_constant_speed_15kmph',
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'straight_constant_speed/straight_constant_speed_20kmph',
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'straight_constant_speed/straight_constant_speed_25kmph',
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'straight_constant_speed/straight_constant_speed_30kmph',
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'straight_constant_speed/straight_constant_speed_35kmph',
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'straight_constant_speed/straight_constant_speed_40kmph',
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'straight_constant_speed/straight_constant_speed_45kmph',
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'straight_constant_speed/straight_constant_speed_5kmph',
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'straight_decelerating/straight_decelerating_30kmph',
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'straight_decelerating/straight_decelerating_35kmph',
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'straight_decelerating/straight_decelerating_40kmph'
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]
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```
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The [preprocessing function](https://github.com/turingmotors/ACT-Bench/blob/main/act_bench/compute_score.py#L92) in the `ACT-Bench` converts the above labels into the following 9 classes to be compared with the estimated action by the `ACT-Estimator`.
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### Context Frames
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The `context_frames` field contains the list of image paths that are used to generate the driving scenes conditioned on the `instruction_trajs`. This image path is relative to the `dataroot` directory of the nuScenes dataset. Make sure to download the [nuScenes](https://www.nuscenes.org/nuscenes) dataset before generating the driving scenes.
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### Command Classes
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The `command` output by the `ACT-Estimator` represents the predicted high-level driving action.
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The output is a logits of 9 classes as follows:
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```python
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LABELS = [
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"curving_to_left", # command = 0
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"curving_to_right", # command = 1
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"straight_constant_high_speed", # command = 2
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"straight_constant_low_speed", # command = 3
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"straight_accelerating", # command = 4
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"straight_decelerating", # command = 5
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"starting", # command = 6
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"stopping", # command = 7
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"stopped", # command = 8
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]
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```
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### Instruction Trajectory and Reference Trajectory
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The `instruction_trajs` (shaped as `(50, 60, 3)`) is created by dividing the `reference_traj` into segments at each time step, and serves as the input to condition the driving scene generation. The `reference_traj` (shaped as `(50, 3)`) is the ground truth trajectory to evaluate the performance of action controllability of the driving world model. So it is expected that if the generated video accurately follows the `instruction_trajs`, the generated trajectory should be close to the `reference_traj`.
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Although both consists of 50 waypoints at each time step, the ACT-Bench evaluation framework only uses the first 44 waypoints to evaluate the performance of action controllability of the driving world model.
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Each waypoint is represented as a 2D vector `(x, y)` in a 2D Cartesian coordinate system.
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- The origin `(0, 0)` is defined as the initial position of the vehicle at the start of the video.
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- The `x`-axis corresponds to the forward direction of the vehicle, with positive values indicating forward movement.
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- The `y`-axis corresponds to the lateral direction of the vehicle, with positive values indicating movement to the left.
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Note that this coordinate system is different from the one used in the ACT-Estimator's `waypoints` output. The conversion between the two coordinate systems is automatically performed by the `ACT-Bench` evaluation framework.
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## Authors
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Here are the team members who contributed to the development of `ACT-Bench`:
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- Hidehisa Arai
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- Keishi Ishihara
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- Tsubasa Takahashi
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- Yu Yamaguchi
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## How to use
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The following code snippet demonstrates how to load the `ACT-Bench` dataset.
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```python
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from datasets import load_dataset
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benchmark_dataset = load_dataset("turing-motors/ACT-Bench", split="train")
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```
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See [here](https://github.com/turingmotors/ACT-Bench/) for the instructions on how to evaluate driving world models using `ACT-Bench`.
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## License
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The ACT-Bench is licensed under the Apache License 2.0.
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## Citation
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If you find our work helpful, please feel free to cite us.
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```bibtex
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@misc{arai2024actbenchactioncontrollableworld,
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title={ACT-Bench: Towards Action Controllable World Models for Autonomous Driving},
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author={Hidehisa Arai and Keishi Ishihara and Tsubasa Takahashi and Yu Yamaguchi},
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year={2024},
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eprint={2412.05337},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2412.05337},
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}
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```
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