--- pretty_name: Language2Drive language: - en license: other license_name: component-specific license_link: https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.carla/THIRD_PARTY_NOTICES tags: - autonomous-driving - vision-language-action - instruction-following - counterfactual-evaluation - carla - realsim - nuscenes - navsim - waymo - benchmark - language2drive ---
# 🚘 Language2Drive ### Do Vision-Language-Action Models Really Follow the Instructions in Autonomous Driving? **Same scene. Same seed. Different instructions.** [![Code](https://img.shields.io/badge/Code-GitHub-202c39?style=flat-square&logo=github)](https://github.com/ZihanYou/Language2Drive) [![Benchmark](https://img.shields.io/badge/Benchmark-5_Backends-2b7a78?style=flat-square)](#benchmark-tracks) [![Leaderboard](https://img.shields.io/badge/Leaderboard-Training_Free_Baselines-68549c?style=flat-square)](#main-results--leaderboard) [![Dataset](https://img.shields.io/badge/Dataset-Versioned_Release_Coming_Soon-e6a43a?style=flat-square)](#release-roadmap) **👥 Authors** Zihan You1,2,*,†, Zehua Fan3,*, Wenqi Lyu4,*, Aoqi Wang5,*,
Ni Wang6, Yifei Yang7, Linge Zhao8, Huan Li9, Sining Ang10, Yuguang Yang1,
Jueyu Chen10,11, Xiangyu Li12, Qianshan Wei13, Jieyuan Pei1,14,15, Yuxin Wang16, Zhiwen Chen15,
Jiaqi Li17, Wenxuan Song15, Yanyuan Qiao18, Benjin Zhu19, Haoang Li15, Yan Wang1,‡ **🏛️ Affiliations** 1 THU · 2 SEU · 3 SJTU · 4 Adelaide · 5 BISTU · 6 Amazon · 7 BJTU
8 WHU · 9 HUST · 10 USTC · 11 NIO · 12 UT Austin · 13 CAS
14 HiThink · 15 HKUST(GZ) · 16 AMD · 17 HKU · 18 EPFL · 19 Li Auto * Core contributors   † Project Lead   ‡ Corresponding author Language2Drive: paired counterfactual instructions, four scopes and five evaluation backends **4 instruction scopes · 3 runtime groups · 5 evaluation backends**
## 🧭 Benchmark in 30 seconds Language2Drive evaluates whether changing a natural-language instruction changes the feasible behavior selected and executed by a driving VLA. Its **Paired Counterfactual Unit (PCU)** fixes the initial driving scene and changes only the instruction, separating individual task completion from completion of both counterfactual alternatives. - **Matched pairs:** same scene, initial state, non-language inputs and simulator seed; different mutually exclusive instructions. - **Four scopes:** atomic actions, persistent behaviors, scene-grounded navigation and long-horizon instruction programs. - **Five backends:** CARLA and RealSim closed loop; nuScenes, NAVSIM and WOD-E2E open loop. - **Training-free evaluation:** all reported baseline systems use the training-free protocol. - **Adapt once:** the unified SDK connects a model to all five native evaluators through one trajectory interface. ## 🔀 PCU: the core evaluation unit | Shared across the pair | Changed between the arms | Evaluated | |---|---|---| | Scene, initial state, non-language inputs and seed | Active natural-language instruction | Requested behavior and rejection of the opposite contract | | Checkpoint and observation configuration | Feasible target behavior | Native safety, progress, deadline and stability requirements | At a shared junction, one arm can request **“Turn left”** and the other **“Go straight.”** Each arm starts independently with reset model memory. Strict paired success requires completing both requests. The model receives public observations and the active instruction; geometric targets, evaluator contracts and the opposite-arm instruction remain with the evaluator. | Scope | What the instruction requires | Example task | |---|---|---| | **A · Atomic action** | Select a local maneuver | Turn, change lane or park | | **B · Persistent behavior** | Maintain a constraint over time | Speed band, lane choice or following behavior | | **C · Scene-grounded navigation** | Resolve a destination or relation in the observed scene | Parking bay, named landmark or obstacle-relative destination | | **D · Long-horizon instruction program** | Execute stages in the specified order | Conditional destinations and multi-stage maneuvers | ### 🏗️ Benchmark construction Source curation, geometric grounding, paired specification, compilation and validation Source scenes are grounded geometrically, paired with feasible instructions, compiled into executable contracts and validated before evaluation. Paraphrases test sensitivity to equivalent wording. ## 🛣️ Benchmark Tracks | Track | Evaluation | Manuscript / frozen scope | Model output | Native guide | |---|---|---|---|---| | **CARLA-L2D** | Closed loop; six purpose-designed maps | **64 paper PCUs**, A–D; 384 core rollouts/system, three expressions | Ego XY → declared controller | [CARLA](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.carla/README.md) | | **RealSim** | Closed loop; AlpaSim / NuRec | **30 PCUs / 23 scenes**, A–B; 60 slots/system, seed 1701 | 6 s / 60 points, 10 Hz | [RealSim](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.RealSim/README.md) | | **nuScenes** | Open loop | **75 release PCUs**: 15 dev + 60 held-out; paper uses held-out canonical | 3 s / 12 points, 4 Hz | [nuScenes](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.OpenloopTrack.nScenes/README.md) | | **NAVSIM** | Open loop | **38 PCUs / 19 recordings**, four wordings | 4 s / 8 points, 2 Hz | [NAVSIM](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.OpenloopTrack.navsim/README.md) | | **WOD-E2E** | Open loop | **241 P0 scored PCUs**: 76 STOP/GO + 165 speed-choice | 5 s / 20 points, 4 Hz | [WOD-E2E](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.OpenloopTrack.WOD-E2E/README.md) | **Scopes are instruction categories; tracks are evaluation environments.** Counts are not interchangeable. CARLA's source inventory is broader than the 64-PCU paper cohort; record tier, split and seed. The SDK defaults to `base` and evaluates dev/test separately. CARLA PSM uses 24 additional routes and requires the native diagnostic evaluation. WOD's public workload can include construction candidates beyond the frozen 241-PCU scored subset. ## 📦 Resources in this repository This Hugging Face repository hosts benchmark workload definitions, replay bundles and runtime resources. The official versioned dataset and model/checkpoint releases are coming soon. | Resource group | Browse / download | Contents | |---|---|---| | **CARLA-L2D** | [CARLA resources](https://huggingface.co/datasets/Mike087/Language2Drive/tree/main/language2drive.carla) | Benchmark and runtime archives, manifests, checksums and integration sources | | **RealSim** | [RealSim resources](https://huggingface.co/datasets/Mike087/Language2Drive/tree/main/langauge2drive.RealSim) | PCUs, public workload, run plan, evaluator sidecar and runtime configuration | | **nuScenes** | [nuScenes resources](https://huggingface.co/datasets/Mike087/Language2Drive/tree/main/language2drive.OpenloopTrack.nScenes) | Asset manifest and `nuscenes-paper-1.0-replay.zip` | | **NAVSIM / WOD-E2E** | [NAVSIM code](https://github.com/ZihanYou/Language2Drive/tree/main/language2drive.OpenloopTrack.navsim) · [WOD-E2E code](https://github.com/ZihanYou/Language2Drive/tree/main/language2drive.OpenloopTrack.WOD-E2E) | Native evaluator guides, source-data requirements and release profiles | The historical RealSim directory is spelled `langauge2drive.RealSim`; use that exact prefix when downloading. ```python from huggingface_hub import snapshot_download snapshot_download( repo_id="Mike087/Language2Drive", repo_type="dataset", local_dir="./language2drive-resources", allow_patterns=["langauge2drive.RealSim/**"], ) ``` Select `language2drive.carla/**` or `language2drive.OpenloopTrack.nScenes/**` for the other available resource groups. Repository authorization uses your Hugging Face account. Model checkpoints are obtained from their original publishers. Source scenes follow the access terms of their upstream datasets. ## 🗂️ Dataset / Evaluation Format | Layer | Contents | Consumer | |---|---|---| | Public observation | Cameras, observed ego state/history and active instruction | Model adapter | | Trajectory request | Track, ego frame, reference point, timestamp grid and model seed | Model adapter | | Evaluator metadata | PCU/arm identity, contracts, pair binding and expected inventory | Track runner / scorer | | Submission | Native trajectory records | Native scorer | | Result | Scores, scheduled coverage, provenance and protocol | Leaderboard / analysis | The SDK accepts **+x forward, +y left, metres**, with explicit frame, reference point and timestamps. For example, a NAVSIM output uses the rear axle and eight points at 2 Hz: ```json { "coordinate_frame": "ego_at_anchor", "reference_point": "rear_axle", "timestamps_s": [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0], "xy_m": [[1, 0], [2, 0], [3, 0], [4, 0], [5, 0], [6, 0], [7, 0], [8, 0]] } ``` nuScenes uses `ego_pose_origin`; RealSim uses `rig_origin`. The [adapter guide](https://github.com/ZihanYou/Language2Drive/blob/main/docs/ADAPTER.md) documents each output contract, and the [protocol](https://github.com/ZihanYou/Language2Drive/blob/main/docs/PROTOCOL.md) specifies native submission files and cohort identities. ## 🏆 Main Results / Leaderboard **All reported systems use the training-free protocol.** Values below are transcribed from the supplied manuscript; all scores are **0–100, higher is better**. Systems are compared **within each track and profile**. [Project-page leaderboard source](https://github.com/ZihanYou/Language2Drive/blob/main/docs/index.html) · [Machine-readable results](https://github.com/ZihanYou/Language2Drive/blob/main/docs/data/results.json) · [Submission guide](https://github.com/ZihanYou/Language2Drive/blob/main/docs/LEADERBOARD.md). Click a model name to read its paper. Explore the [interactive metric guide](https://ZihanYou.github.io/Language2Drive/#metric-explorer) for paired success, graded compliance and the L2D score.
📊 CARLA-L2D paper: 64 PCUs · 3 expressions · seed 1. | System | SISR | CFPS | SemISR | Sem-CFPS | SCS | PCS | PSM | DrivingScore | L2D | |---|---:|---:|---:|---:|---:|---:|---:|---:|---:| | [Alpamayo 1.5](https://arxiv.org/abs/2511.00088 "Alpamayo family paper") · [model card](https://huggingface.co/nvidia/Alpamayo-1.5-10B) | 8.07 | 1.04 | 42.19 | 30.73 | 26.18 | 12.50 | 70.10 | 62.69 | 12.20 | | [SimLingo](https://arxiv.org/abs/2503.09594) | 7.81 | 1.04 | 48.70 | 35.94 | 23.51 | 11.94 | 62.30 | 65.04 | 12.15 | | [LMDrive](https://arxiv.org/abs/2312.07488) | 12.24 | 0.00 | 29.17 | 18.23 | 21.45 | 9.26 | 88.84 | 50.12 | 10.39 | | [OneVL](https://arxiv.org/abs/2604.18486) | 0.52 | 0.00 | 25.00 | 3.65 | 16.69 | 7.05 | 77.72 | 50.69 | 4.87 | | [Qwen-Drive-1.0-4B](https://arxiv.org/abs/2609.00111) | 1.82 | 0.00 | 15.62 | 3.12 | 17.05 | 7.09 | 76.68 | 43.67 | 4.31 | | [Impromptu-VLA](https://arxiv.org/abs/2505.23757) | 0.26 | 0.00 | 19.79 | 6.25 | 14.48 | 4.61 | 77.43 | 42.02 | 3.87 |
📊 RealSim realsim-paper-1.0: 30 PCUs · seed 1701. | System | SISR | CFPS | SemISR | Sem-CFPS | SCS | PCS | Safety | DrivingScore | L2D | |---|---:|---:|---:|---:|---:|---:|---:|---:|---:| | [Alpamayo2-Super](https://arxiv.org/abs/2511.00088 "Alpamayo family paper") · [model card](https://huggingface.co/nvidia/Alpamayo2-Super) | 13.33 | 0.00 | 18.33 | 0.00 | 21.43 | 0.00 | 93.33 | 97.10 | 9.22 | | [Alpamayo 1.5](https://arxiv.org/abs/2511.00088 "Alpamayo family paper") · [model card](https://huggingface.co/nvidia/Alpamayo-1.5-10B) | 11.67 | 0.00 | 15.00 | 0.00 | 18.12 | 1.11 | 100.00 | 97.17 | 8.38 | | [SimLingo](https://arxiv.org/abs/2503.09594) | 6.67 | 3.33 | 13.33 | 6.67 | 16.67 | 10.00 | 68.33 | 83.09 | 7.58 | | [AutoVLA](https://arxiv.org/abs/2506.13757) | 1.67 | 0.00 | 8.33 | 6.67 | 9.73 | 6.67 | 41.67 | 76.94 | 3.36 | | [Qwen-Drive-1.0-4B](https://arxiv.org/abs/2609.00111) | 0.00 | 0.00 | 1.67 | 0.00 | 4.44 | 0.00 | 43.33 | 69.16 | 0.92 | | [Impromptu-VLA](https://arxiv.org/abs/2505.23757) | 0.00 | 0.00 | 1.67 | 0.00 | 3.71 | 0.00 | 30.00 | 68.85 | 0.78 | | [OneVL](https://arxiv.org/abs/2604.18486) | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 43.33 | 43.82 | 0.44 | | [ReCogDrive](https://arxiv.org/abs/2506.08052) | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 33.33 | 43.57 | 0.38 |
📊 nuScenes v1.0-test · 60 held-out PCUs · canonical. | System | SemSISR | SemCFPS | SCS | PCS | |---|---:|---:|---:|---:| | [Impromptu-VLA](https://arxiv.org/abs/2505.23757) | 15.83 | 0.00 | 20.21 | 0.00 | | [UniDriveVLA](https://arxiv.org/abs/2604.02190) | 16.67 | 0.00 | 25.00 | 0.00 | | [OpenDriveVLA-0.5B](https://arxiv.org/abs/2503.23463) | 13.33 | 3.33 | 19.06 | 4.30 | | [OmniDrive](https://arxiv.org/abs/2405.01533) | 7.50 | 0.00 | 29.24 | 8.61 |
📊 NAVSIM paper historical scorer · 38 PCUs · 4 wordings. | System | SemSISR | SemCFPS | SCS | PCS | |---|---:|---:|---:|---:| | [Qwen-Drive-1.0-4B](https://arxiv.org/abs/2609.00111) | 0.000 | 0.000 | 5.472 | 0.000 | | [AutoVLA](https://arxiv.org/abs/2506.13757) | 3.947 | 0.000 | 8.172 | 0.000 | | [DriveMA-2B](https://arxiv.org/abs/2605.31271) | 8.553 | 0.000 | 11.244 | 2.242 | | [ReCogDrive](https://arxiv.org/abs/2506.08052) | 0.000 | 0.000 | 4.400 | 0.000 | | [OneVL](https://arxiv.org/abs/2604.18486) | 3.618 | 0.000 | 8.428 | 0.000 |
📊 WOD-E2E P0 · 241 PCUs · canonical. | System | SemSISR | SemCFPS | SCS | PCS | |---|---:|---:|---:|---:| | [DriveMA-2B](https://arxiv.org/abs/2605.31271) | 38.38 | 1.24 | 49.33 | 7.88 | | [Fast-dDrive](https://arxiv.org/abs/2605.23163) | 34.85 | 0.00 | 46.42 | 5.27 | | [Qwen-Drive-SFT](https://arxiv.org/abs/2609.00111) | 34.44 | 0.00 | 50.58 | 9.37 | | [Qwen-Drive-RL](https://arxiv.org/abs/2609.00111) | 35.06 | 0.00 | 49.58 | 7.58 |
The CARLA table includes the six principal systems; the paper's Senna high-level bridge is a separate diagnostic configuration. **NAVSIM numbers use the historical manuscript scorer.** New SDK runs use `score_corrected.py`; keep corrected evaluations in a separate leaderboard profile. Full protocol, coverage and failure denominators must accompany submissions. Rankings follow each track’s native metrics and evaluation profile. ### 📐 Reading the metrics **SISR / CFPS** measure strict individual / paired completion. **SCS / PCS** measure graded individual / paired compliance. Closed-loop **SemISR / Sem-CFPS** are relaxed proxies; open-loop **SemSISR / SemCFPS** apply exclusive semantic success. Wording robustness is evaluated using equivalent paraphrases. **L2D** combines the native language and driving score families with the track's nonlinear aggregation. Full definitions are in the [evaluation protocol](https://github.com/ZihanYou/Language2Drive/blob/main/docs/PROTOCOL.md). ## 🚀 Evaluate your model Install the coordinator from the source repository or a release wheel, select your runtime groups, and implement one model adapter: ```sh git clone https://github.com/ZihanYou/Language2Drive.git cd Language2Drive python -m pip install -e '.[openloop]' language2drive init --workspace ./l2d-workspace language2drive setup --workspace ./l2d-workspace --tracks all --runtime --download ``` `setup` selects official Hugging Face / PyPI endpoints when reachable and mirror / Tsinghua endpoints otherwise. Authenticated benchmark downloads use the official Hugging Face endpoint. CARLA and RealSim use separate simulator environments. Licensed source data, GPU services and model checkpoints are configured according to the selected backend. - [Quick start and all five native reproduction commands](https://github.com/ZihanYou/Language2Drive#quick-start) - [Full GPU evaluation guide](https://github.com/ZihanYou/Language2Drive/blob/main/docs/GPU_EVALUATION.md) - [Installation and resource setup](https://github.com/ZihanYou/Language2Drive/blob/main/docs/INSTALLATION.md) - [Leaderboard submission guide](https://github.com/ZihanYou/Language2Drive/blob/main/docs/LEADERBOARD.md) - [Interactive project preview, paired cases and demonstration film](https://github.com/ZihanYou/Language2Drive/blob/main/docs/SHOWCASE.md) ## 🗓️ Release Roadmap | Status | Deliverable | |:---:|---| | ✅ | Benchmark source, five native evaluators and a unified model-adapter SDK | | ✅ | Wheel build and selectable environment/resource setup | | ✅ | Training-free baseline tables and paired case visualizations | | ✅ | Evaluation resources in this Hugging Face repository | | ⏳ | Official versioned dataset release | | ⏳ | Official model and checkpoint release | ## 📚 Citation If Language2Drive supports your research, please cite our paper. ```bibtex @misc{language2drive, title = {Language2Drive: Do Vision-Language-Action Models Really Follow the Instructions in Autonomous Driving?}, author = {You, Zihan and Fan, Zehua and Lyu, Wenqi and Wang, Aoqi and Wang, Ni and Yang, Yifei and Zhao, Linge and Li, Huan and Ang, Sining and Yang, Yuguang and Chen, Jueyu and Li, Xiangyu and Wei, Qianshan and Pei, Jieyuan and Wang, Yuxin and Chen, Zhiwen and Li, Jiaqi and Song, Wenxuan and Qiao, Yanyuan and Zhu, Benjin and Li, Haoang and Wang, Yan}, howpublished = {Research manuscript}, url = {https://github.com/ZihanYou/Language2Drive} } ``` ## 📄 License Original Language2Drive code uses the [MIT License](https://github.com/ZihanYou/Language2Drive/blob/main/LICENSE). Dataset, simulator, runtime and third-party integration resources retain their respective licenses. See the [CARLA resource license](https://huggingface.co/datasets/Mike087/Language2Drive/blob/main/language2drive.carla/LICENSE), [third-party notices](https://huggingface.co/datasets/Mike087/Language2Drive/blob/main/language2drive.carla/THIRD_PARTY_NOTICES) and [RealSim notices](https://github.com/ZihanYou/Language2Drive/blob/main/language2drive.RealSim/NOTICE.md). This card preserves the repository's **component-specific** license designation. Manuscript figures are research materials and are separate from the code license.