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---
license: apache-2.0
---
# ACT-Bench
`ACT-Bench` is a dedicated framework for quantitatively evaluating the action controllability of world models for autonomous driving.
It focuses on measuring how well a world model can generate driving scenes conditioned on specified trajectories.
<img src="https://github.com/turingmotors/ACT-Bench/blob/main/assets/overview.png" alt="Overview of the Dataset" width="600">
For more details, please refer our [paper]() and [repository](https://github.com/turingmotors/ACT-Bench).
## Data fields
| **Key** | **Value** |
|-------------------------------|------------------------------------------------------------------|
| **sample_id** | 0 |
| **label** | 'straight_constant_speed/straight_constant_speed_10kmph' |
| **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'] |
| **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]], ... |
| **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]] |
| **intrinsic** | [[1266.4172030466, 0.0, 816.2670197448],[0.0, 1266.4172030466, 491.5070657929],[0.0, 0.0, 1.0]] |
### Labels
The `label` field is a string that represents one of the following high-level driving actions:
```python
[
'curving_to_left/curving_to_left_moderate',
'curving_to_left/curving_to_left_sharp',
'curving_to_left/curving_to_left_wide',
'curving_to_right/curving_to_right_moderate',
'curving_to_right/curving_to_right_sharp',
'curving_to_right/curving_to_right_wide',
'shifting_towards_left/shifting_towards_left_short',
'shifting_towards_right/shifting_towards_right_long',
'shifting_towards_right/shifting_towards_right_short',
'starting/starting_20kmph',
'starting/starting_25kmph',
'starting/starting_30kmph',
'stopping/stopping_15kmph',
'stopping/stopping_20kmph',
'stopping/stopping_25kmph',
'stopping/stopping_30kmph',
'stopping/stopping_35kmph',
'stopping/stopping_40kmph',
'stopping/stopping_45kmph',
'straight_accelerating/straight_accelerating_15kmph',
'straight_accelerating/straight_accelerating_20kmph',
'straight_accelerating/straight_accelerating_25kmph',
'straight_constant_speed/straight_constant_speed_10kmph',
'straight_constant_speed/straight_constant_speed_15kmph',
'straight_constant_speed/straight_constant_speed_20kmph',
'straight_constant_speed/straight_constant_speed_25kmph',
'straight_constant_speed/straight_constant_speed_30kmph',
'straight_constant_speed/straight_constant_speed_35kmph',
'straight_constant_speed/straight_constant_speed_40kmph',
'straight_constant_speed/straight_constant_speed_45kmph',
'straight_constant_speed/straight_constant_speed_5kmph',
'straight_decelerating/straight_decelerating_30kmph',
'straight_decelerating/straight_decelerating_35kmph',
'straight_decelerating/straight_decelerating_40kmph'
]
```
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`.
### Context Frames
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.
### Command Classes
The `command` output by the `ACT-Estimator` represents the predicted high-level driving action.
The output is a logits of 9 classes as follows:
```python
LABELS = [
"curving_to_left", # command = 0
"curving_to_right", # command = 1
"straight_constant_high_speed", # command = 2
"straight_constant_low_speed", # command = 3
"straight_accelerating", # command = 4
"straight_decelerating", # command = 5
"starting", # command = 6
"stopping", # command = 7
"stopped", # command = 8
]
```
### Instruction Trajectory and Reference Trajectory
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`.
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.
Each waypoint is represented as a 2D vector `(x, y)` in a 2D Cartesian coordinate system.
- The origin `(0, 0)` is defined as the initial position of the vehicle at the start of the video.
- The `x`-axis corresponds to the forward direction of the vehicle, with positive values indicating forward movement.
- The `y`-axis corresponds to the lateral direction of the vehicle, with positive values indicating movement to the left.
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.
## Authors
Here are the team members who contributed to the development of `ACT-Bench`:
- Hidehisa Arai
- Keishi Ishihara
- Tsubasa Takahashi
- Yu Yamaguchi
## How to use
The following code snippet demonstrates how to load the `ACT-Bench` dataset.
```python
from datasets import load_dataset
benchmark_dataset = load_dataset("turing-motors/ACT-Bench", data_files="act_bench.jsonl", split="train")
```
See [here](https://github.com/turingmotors/ACT-Bench/) for the instructions on how to evaluate driving world models using `ACT-Bench`.
## License
The ACT-Bench is licensed under the Apache License 2.0.
## Citation
If you find our work helpful, please feel free to cite us.
```bibtex
@misc{arai2024actbenchactioncontrollableworld,
title={ACT-Bench: Towards Action Controllable World Models for Autonomous Driving},
author={Hidehisa Arai and Keishi Ishihara and Tsubasa Takahashi and Yu Yamaguchi},
year={2024},
eprint={2412.05337},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.05337},
}
```
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