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| { | |
| "task": "CARLA Longest6", | |
| "categories": [ | |
| "Robots" | |
| ], | |
| "description": "Longest6 is an evaluation benchmark for sensorimotor autonomous driving methods using the CARLA 0.9.10.1 simulator. It consists of 36 long routes in the publicly available Town 01-06 which, are populated with the maximum traffic density. The benchmark tests level 4 driving capabilities, methods are therefore allowed to train with data from the evaluation towns. Evaluation metrics follow the standard metrics from the CARLA leaderboard 1.0, except that stop sign infractions are not considered.", | |
| "subtasks": [], | |
| "synonyms": [], | |
| "source_link": null, | |
| "datasets": [ | |
| { | |
| "sota": { | |
| "rows": [ | |
| { | |
| "code_links": [], | |
| "model_links": [], | |
| "model_name": "DiffE2E", | |
| "metrics": { | |
| "Driving Score": "83", | |
| "Route Completion": "96", | |
| "Infraction Score": "0.86" | |
| }, | |
| "paper_date": "2025-06-11", | |
| "paper_title": "DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policy", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2505.19516" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/carla_garage", | |
| "title": "autonomousvision/carla_garage" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "TransFuser++ WP (TF++WP)", | |
| "metrics": { | |
| "Driving Score": "73", | |
| "Route Completion": "97", | |
| "Infraction Score": "0.56" | |
| }, | |
| "paper_date": "2023-06-13", | |
| "paper_title": "Hidden Biases of End-to-End Driving Models", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2306.07957v2" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/opendrivelab/driveadapter", | |
| "title": "opendrivelab/driveadapter" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "DriveAdapter+TCP", | |
| "metrics": { | |
| "Driving Score": "71", | |
| "Route Completion": "88", | |
| "Infraction Score": "0.85" | |
| }, | |
| "paper_date": "2023-08-01", | |
| "paper_title": "DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2308.00398v2" | |
| }, | |
| { | |
| "code_links": [], | |
| "model_links": [], | |
| "model_name": "DriveGPT4-V2", | |
| "metrics": { | |
| "Driving Score": "70", | |
| "Route Completion": "91", | |
| "Infraction Score": "0.77" | |
| }, | |
| "paper_date": null, | |
| "paper_title": "", | |
| "uses_additional_data": false, | |
| "paper_url": "" | |
| }, | |
| { | |
| "code_links": [], | |
| "model_links": [], | |
| "model_name": "EnDfuser + safety-rule", | |
| "metrics": { | |
| "Driving Score": "70", | |
| "Route Completion": "90", | |
| "Infraction Score": "0.76" | |
| }, | |
| "paper_date": "2025-05-31", | |
| "paper_title": "Using Diffusion Ensembles to Estimate Uncertainty for End-to-End Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2506.00560v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/carla_garage", | |
| "title": "autonomousvision/carla_garage" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "TransFuser++ (TF++)", | |
| "metrics": { | |
| "Driving Score": "69", | |
| "Route Completion": "94", | |
| "Infraction Score": "0.72" | |
| }, | |
| "paper_date": "2023-06-13", | |
| "paper_title": "Hidden Biases of End-to-End Driving Models", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2306.07957v2" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/opendrivelab/thinktwice", | |
| "title": "opendrivelab/thinktwice" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "ThinkTwice", | |
| "metrics": { | |
| "Driving Score": "67", | |
| "Route Completion": "77", | |
| "Infraction Score": "0.84" | |
| }, | |
| "paper_date": "2023-05-10", | |
| "paper_title": "Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2305.06242v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/opendrivelab/driveadapter", | |
| "title": "opendrivelab/driveadapter" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "DriveAdapter", | |
| "metrics": { | |
| "Driving Score": "59", | |
| "Route Completion": "82", | |
| "Infraction Score": "0.68" | |
| }, | |
| "paper_date": "2023-08-01", | |
| "paper_title": "DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2308.00398v2" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/plant", | |
| "title": "autonomousvision/plant" | |
| }, | |
| { | |
| "url": "https://github.com/autonomousvision/CaRL", | |
| "title": "autonomousvision/CaRL" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Perception PlanT", | |
| "metrics": { | |
| "Driving Score": "58", | |
| "Route Completion": "88", | |
| "Infraction Score": "0.65" | |
| }, | |
| "paper_date": "2022-10-25", | |
| "paper_title": "PlanT: Explainable Planning Transformers via Object-Level Representations", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2210.14222v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/dotchen/LAV", | |
| "title": "dotchen/LAV" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Learning from all Vehicle v2 (LAV v2)", | |
| "metrics": { | |
| "Driving Score": "58", | |
| "Route Completion": "83", | |
| "Infraction Score": "0.68" | |
| }, | |
| "paper_date": "2022-03-22", | |
| "paper_title": "Learning from All Vehicles", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2203.11934v3" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/h2xlab/CaT", | |
| "title": "h2xlab/CaT" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Coaching a Teachable Student (CaT)", | |
| "metrics": { | |
| "Driving Score": "58", | |
| "Route Completion": "79", | |
| "Infraction Score": "0.77" | |
| }, | |
| "paper_date": "2023-06-16", | |
| "paper_title": "Coaching a Teachable Student", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2306.10014v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/fujiawei0724/interactionnet", | |
| "title": "fujiawei0724/interactionnet" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "InteractionNet", | |
| "metrics": { | |
| "Driving Score": "51", | |
| "Route Completion": "87", | |
| "Infraction Score": "0.60" | |
| }, | |
| "paper_date": "2023-09-07", | |
| "paper_title": "InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2309.03475v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/OpenPerceptionX/TCP", | |
| "title": "OpenPerceptionX/TCP" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Trajectory-guided Control Prediction (TCP)", | |
| "metrics": { | |
| "Driving Score": "48", | |
| "Route Completion": "72", | |
| "Infraction Score": "0.65" | |
| }, | |
| "paper_date": "2022-06-16", | |
| "paper_title": "Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2206.08129v2" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/transfuser", | |
| "title": "autonomousvision/transfuser" | |
| }, | |
| { | |
| "url": "https://github.com/autonomousvision/navsim", | |
| "title": "autonomousvision/navsim" | |
| }, | |
| { | |
| "url": "https://github.com/pagand/e2etransfuser", | |
| "title": "pagand/e2etransfuser" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "TransFuser (TF)", | |
| "metrics": { | |
| "Driving Score": "47", | |
| "Route Completion": "93", | |
| "Infraction Score": "0.50" | |
| }, | |
| "paper_date": "2022-05-31", | |
| "paper_title": "TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2205.15997v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/opendilab/InterFuser", | |
| "title": "opendilab/InterFuser" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Interfuser", | |
| "metrics": { | |
| "Driving Score": "47", | |
| "Route Completion": "74", | |
| "Infraction Score": "0.63" | |
| }, | |
| "paper_date": "2022-07-28", | |
| "paper_title": "Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2207.14024v5" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/transfuser", | |
| "title": "autonomousvision/transfuser" | |
| }, | |
| { | |
| "url": "https://github.com/autonomousvision/navsim", | |
| "title": "autonomousvision/navsim" | |
| }, | |
| { | |
| "url": "https://github.com/pagand/e2etransfuser", | |
| "title": "pagand/e2etransfuser" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Latent TransFuser (LTF)", | |
| "metrics": { | |
| "Driving Score": "37", | |
| "Route Completion": "95", | |
| "Infraction Score": "0.38" | |
| }, | |
| "paper_date": "2022-05-31", | |
| "paper_title": "TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2205.15997v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/dotchen/LAV", | |
| "title": "dotchen/LAV" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Learning from all Vehicles v1 (LAV v1)", | |
| "metrics": { | |
| "Driving Score": "33", | |
| "Route Completion": "70", | |
| "Infraction Score": "0.51" | |
| }, | |
| "paper_date": "2022-03-22", | |
| "paper_title": "Learning from All Vehicles", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2203.11934v3" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/transfuser", | |
| "title": "autonomousvision/transfuser" | |
| }, | |
| { | |
| "url": "https://github.com/autonomousvision/navsim", | |
| "title": "autonomousvision/navsim" | |
| }, | |
| { | |
| "url": "https://github.com/pagand/e2etransfuser", | |
| "title": "pagand/e2etransfuser" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Geometric Fusion (GF)", | |
| "metrics": { | |
| "Driving Score": "27", | |
| "Route Completion": "91", | |
| "Infraction Score": "0.30" | |
| }, | |
| "paper_date": "2022-05-31", | |
| "paper_title": "TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2205.15997v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/neat", | |
| "title": "autonomousvision/neat" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Neural Attention Fields (NEAT)", | |
| "metrics": { | |
| "Driving Score": "24", | |
| "Route Completion": "62", | |
| "Infraction Score": "0.71" | |
| }, | |
| "paper_date": "2021-09-09", | |
| "paper_title": "NEAT: Neural Attention Fields for End-to-End Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2109.04456v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/autonomousvision/transfuser", | |
| "title": "autonomousvision/transfuser" | |
| }, | |
| { | |
| "url": "https://github.com/autonomousvision/navsim", | |
| "title": "autonomousvision/navsim" | |
| }, | |
| { | |
| "url": "https://github.com/pagand/e2etransfuser", | |
| "title": "pagand/e2etransfuser" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "Late Fusion (LF)", | |
| "metrics": { | |
| "Driving Score": "22", | |
| "Route Completion": "83", | |
| "Infraction Score": "0.27" | |
| }, | |
| "paper_date": "2022-05-31", | |
| "paper_title": "TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2205.15997v1" | |
| }, | |
| { | |
| "code_links": [ | |
| { | |
| "url": "https://github.com/dotchen/WorldOnRails", | |
| "title": "dotchen/WorldOnRails" | |
| } | |
| ], | |
| "model_links": [], | |
| "model_name": "World on Rails (WOR)", | |
| "metrics": { | |
| "Driving Score": "21", | |
| "Route Completion": "48", | |
| "Infraction Score": "0.56" | |
| }, | |
| "paper_date": "2021-05-03", | |
| "paper_title": "Learning to drive from a world on rails", | |
| "uses_additional_data": false, | |
| "paper_url": "https://arxiv.org/abs/2105.00636v3" | |
| } | |
| ], | |
| "metrics": [ | |
| "Driving Score", | |
| "Route Completion", | |
| "Infraction Score" | |
| ] | |
| }, | |
| "dataset_links": [ | |
| { | |
| "url": "https://paperswithcode.com/sota/carla-longest6-on-carla", | |
| "title": "Papers with Code Leaderboard URL" | |
| } | |
| ], | |
| "description": "", | |
| "subdatasets": [], | |
| "dataset_citations": [], | |
| "dataset": "CARLA" | |
| } | |
| ] | |
| } |