{"total":499,"rows":[{"id":"2303.12077","title":"VAD: Vectorized Scene Representation for Efficient Autonomous Driving","created":"2023-03-21","cited_by_count":622,"area":"driving"},{"id":"2306.16927","title":"End-to-end Autonomous Driving: Challenges and Frontiers","created":"2023-06-29","cited_by_count":490,"area":"driving"},{"id":"2205.15997","title":"TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving","created":"2022-05-31","cited_by_count":485,"area":"driving"},{"id":"2104.09224","title":"Multi-Modal Fusion Transformer for End-to-End Autonomous Driving","created":"2021-04-19","cited_by_count":377,"area":"driving"},{"id":"2207.07601","title":"ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning","created":"2022-07-15","cited_by_count":368,"area":"driving"},{"id":"2406.15349","title":"NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking","created":"2024-06-21","cited_by_count":354,"area":"driving"},{"id":"2312.07488","title":"LMDrive: Closed-Loop End-to-End Driving with Large Language Models","created":"2023-12-12","cited_by_count":305,"area":"driving"},{"id":"2402.13243","title":"VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning","created":"2024-02-20","cited_by_count":289,"area":"driving"},{"id":"2406.03877","title":"Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving","created":"2024-06-06","cited_by_count":252,"area":"driving"},{"id":"2206.08129","title":"Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline","created":"2022-06-16","cited_by_count":248,"area":"driving"},{"id":"2101.06679","title":"End-to-end Interpretable Neural Motion Planner","created":"2021-01-17","cited_by_count":242,"area":"driving"},{"id":"2108.08265","title":"End-to-End Urban Driving by Imitating a Reinforcement Learning Coach","created":"2021-08-18","cited_by_count":194,"area":"driving"},{"id":"2109.04456","title":"NEAT: Neural Attention Fields for End-to-End Autonomous Driving","created":"2021-09-09","cited_by_count":174,"area":"driving"},{"id":"2305.06242","title":"Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving","created":"2023-05-10","cited_by_count":169,"area":"driving"},{"id":"2210.07729","title":"Model-Based Imitation Learning for Urban Driving","created":"2022-10-14","cited_by_count":150,"area":"driving"},{"id":"2311.15260","title":"NeuRAD: Neural Rendering for Autonomous Driving","created":"2023-11-26","cited_by_count":150,"area":"driving"},{"id":"2503.09594","title":"SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment","created":"2025-03-12","cited_by_count":150,"area":"driving"},{"id":"2506.04218","title":"Pseudo-Simulation for Autonomous Driving","created":"2025-06-04","cited_by_count":150,"area":"driving"},{"id":"2308.00398","title":"DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving","created":"2023-08-01","cited_by_count":144,"area":"driving"},{"id":"2112.05077","title":"Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior","created":"2021-12-09","cited_by_count":139,"area":"driving"},{"id":"2203.11934","title":"Learning from All Vehicles","created":"2022-03-22","cited_by_count":135,"area":"driving"},{"id":"2212.11419","title":"Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios","created":"2022-12-21","cited_by_count":129,"area":"driving"},{"id":"2109.13333","title":"Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients","created":"2021-09-27","cited_by_count":122,"area":"driving"},{"id":"2105.00636","title":"Learning to drive from a world on rails","created":"2021-05-03","cited_by_count":114,"area":"driving"},{"id":"2303.09824","title":"Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives","created":"2023-03-17","cited_by_count":114,"area":"driving"},{"id":"2104.13906","title":"Reward (Mis)design for Autonomous Driving","created":"2021-04-28","cited_by_count":104,"area":"driving"},{"id":"2403.04133","title":"Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving","created":"2024-03-07","cited_by_count":104,"area":"driving"},{"id":"2307.04370","title":"Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey","created":"2023-07-10","cited_by_count":103,"area":"driving"},{"id":"2408.00415","title":"DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving","created":"2024-08-01","cited_by_count":98,"area":"driving"},{"id":"2204.13683","title":"KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients","created":"2022-04-28","cited_by_count":96,"area":"driving"},{"id":"2306.07957","title":"Hidden Biases of End-to-End Driving Models","created":"2023-06-13","cited_by_count":96,"area":"driving"},{"id":"2503.12820","title":"Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation","created":"2025-03-17","cited_by_count":96,"area":"driving"},{"id":"2205.02222","title":"COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles","created":"2022-05-04","cited_by_count":95,"area":"driving"},{"id":"2305.10507","title":"ReasonNet: End-to-End Driving with Temporal and Global Reasoning","created":"2023-05-17","cited_by_count":93,"area":"driving"},{"id":"2405.14062","title":"ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles","created":"2024-05-22","cited_by_count":93,"area":"driving"},{"id":"2402.05746","title":"Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents","created":"2024-02-08","cited_by_count":91,"area":"driving"},{"id":"2404.14327","title":"PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving","created":"2024-04-22","cited_by_count":84,"area":"driving"},{"id":"2506.09042","title":"Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models","created":"2025-06-10","cited_by_count":84,"area":"driving"},{"id":"2502.13144","title":"RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning","created":"2025-02-18","cited_by_count":79,"area":"driving"},{"id":"2302.00673","title":"ADAPT: Action-aware Driving Caption Transformer","created":"2023-02-01","cited_by_count":78,"area":"driving"},{"id":"2105.12332","title":"SimNet: Learning Reactive Self-driving Simulations from Real-world Observations","created":"2021-05-26","cited_by_count":77,"area":"driving"},{"id":"2112.11561","title":"Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions","created":"2021-12-21","cited_by_count":73,"area":"driving"},{"id":"2304.01168","title":"DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving","created":"2023-04-03","cited_by_count":73,"area":"driving"},{"id":"2206.09682","title":"SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles","created":"2022-06-20","cited_by_count":66,"area":"driving"},{"id":"2202.07008","title":"Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing","created":"2022-02-14","cited_by_count":64,"area":"driving"},{"id":"2403.04593","title":"Embodied Understanding of Driving Scenarios","created":"2024-03-07","cited_by_count":63,"area":"driving"},{"id":"2404.07762","title":"NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving","created":"2024-04-11","cited_by_count":62,"area":"driving"},{"id":"2101.01993","title":"A Survey of Deep RL and IL for Autonomous Driving Policy Learning","created":"2021-01-06","cited_by_count":61,"area":"driving"},{"id":"2111.08575","title":"GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving","created":"2021-11-16","cited_by_count":60,"area":"driving"},{"id":"2310.17642","title":"Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models","created":"2023-10-26","cited_by_count":59,"area":"driving"},{"id":"2110.05754","title":"Deep Federated Learning for Autonomous Driving","created":"2021-10-12","cited_by_count":54,"area":"driving"},{"id":"2310.12432","title":"CAT: Closed-loop Adversarial Training for Safe End-to-End Driving","created":"2023-10-19","cited_by_count":54,"area":"driving"},{"id":"2104.10753","title":"Multi-task Learning with Attention for End-to-end Autonomous Driving","created":"2021-04-21","cited_by_count":49,"area":"driving"},{"id":"2202.10341","title":"Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization","created":"2022-02-17","cited_by_count":49,"area":"driving"},{"id":"2408.01584","title":"GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS","created":"2024-08-02","cited_by_count":45,"area":"driving"},{"id":"2210.09539","title":"Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving","created":"2022-10-18","cited_by_count":44,"area":"driving"},{"id":"2401.03641","title":"DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving","created":"2024-01-08","cited_by_count":43,"area":"driving"},{"id":"2404.00717","title":"End-to-End Autonomous Driving through V2X Cooperation","created":"2024-03-31","cited_by_count":42,"area":"driving"},{"id":"2503.11650","title":"Centaur: Robust End-to-End Autonomous Driving with Test-Time Training","created":"2025-03-14","cited_by_count":42,"area":"driving"},{"id":"2505.15111","title":"iPad: Iterative Proposal-centric End-to-End Autonomous Driving","created":"2025-05-21","cited_by_count":42,"area":"driving"},{"id":"2405.15324","title":"Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving","created":"2024-05-24","cited_by_count":41,"area":"driving"},{"id":"2510.04333","title":"RAP: 3D Rasterization Augmented End-to-End Planning","created":"2025-10-05","cited_by_count":41,"area":"driving"},{"id":"2503.12030","title":"Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Training","created":"2025-03-15","cited_by_count":39,"area":"driving"},{"id":"2506.11526","title":"Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis","created":"2025-06-13","cited_by_count":38,"area":"driving"},{"id":"2503.08612","title":"HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder","created":"2025-03-11","cited_by_count":35,"area":"driving"},{"id":"2104.07830","title":"Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles","created":"2021-04-16","cited_by_count":33,"area":"driving"},{"id":"2401.03160","title":"HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving","created":"2024-01-06","cited_by_count":32,"area":"driving"},{"id":"2408.09675","title":"Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey","created":"2024-08-19","cited_by_count":32,"area":"driving"},{"id":"2107.08142","title":"Autonomy 2.0: Why is self-driving always 5 years away?","created":"2021-07-16","cited_by_count":30,"area":"driving"},{"id":"2412.09602","title":"Hidden Biases of End-to-End Driving Datasets","created":"2024-12-12","cited_by_count":30,"area":"driving"},{"id":"2601.22032","title":"Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving","created":"2026-01-29","cited_by_count":30,"area":"driving"},{"id":"2306.15713","title":"Rethinking Closed-loop Training for Autonomous Driving","created":"2023-06-27","cited_by_count":29,"area":"driving"},{"id":"2312.04316","title":"Towards Knowledge-driven Autonomous Driving","created":"2023-12-07","cited_by_count":29,"area":"driving"},{"id":"2406.17680","title":"End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotation","created":"2024-06-25","cited_by_count":28,"area":"driving"},{"id":"2101.05337","title":"A Survey on Simulators for Testing Self-Driving Cars","created":"2021-01-13","cited_by_count":27,"area":"driving"},{"id":"2102.03483","title":"Corner Case Generation and Analysis for Safety Assessment of Autonomous Vehicles","created":"2021-02-06","cited_by_count":27,"area":"driving"},{"id":"2102.09243","title":"Improved Deep Reinforcement Learning with Expert Demonstrations for Urban Autonomous Driving","created":"2021-02-18","cited_by_count":27,"area":"driving"},{"id":"2406.03008","title":"DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences","created":"2024-06-05","cited_by_count":27,"area":"driving"},{"id":"2409.18343","title":"Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving","created":"2024-09-26","cited_by_count":27,"area":"driving"},{"id":"2301.01006","title":"Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling","created":"2023-01-03","cited_by_count":26,"area":"driving"},{"id":"2503.03074","title":"BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving","created":"2025-03-05","cited_by_count":26,"area":"driving"},{"id":"2603.29163","title":"SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving","created":"2026-03-31","cited_by_count":26,"area":"driving"},{"id":"2104.12861","title":"Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation","created":"2021-04-18","cited_by_count":25,"area":"driving"},{"id":"2303.01212","title":"Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review","created":"2023-03-02","cited_by_count":25,"area":"driving"},{"id":"2309.10443","title":"Rethinking Imitation-based Planner for Autonomous Driving","created":"2023-09-19","cited_by_count":25,"area":"driving"},{"id":"2503.06744","title":"CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving","created":"2025-03-09","cited_by_count":25,"area":"driving"},{"id":"2504.13406","title":"LangCoop: Collaborative Driving with Language","created":"2025-04-18","cited_by_count":25,"area":"driving"},{"id":"2108.02940","title":"Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles","created":"2021-08-06","cited_by_count":24,"area":"driving"},{"id":"2208.12263","title":"Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Driving","created":"2022-08-24","cited_by_count":24,"area":"driving"},{"id":"2401.08045","title":"Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities","created":"2024-01-16","cited_by_count":24,"area":"driving"},{"id":"2105.08169","title":"Safe Occlusion-aware Autonomous Driving via Game-Theoretic Active Perception","created":"2021-05-17","cited_by_count":23,"area":"driving"},{"id":"2111.06889","title":"DriverGym: Democratising Reinforcement Learning for Autonomous Driving","created":"2021-11-12","cited_by_count":23,"area":"driving"},{"id":"2203.16792","title":"TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving","created":"2022-03-31","cited_by_count":23,"area":"driving"},{"id":"2405.05885","title":"VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes","created":"2024-05-09","cited_by_count":23,"area":"driving"},{"id":"2512.20563","title":"LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving","created":"2025-12-23","cited_by_count":23,"area":"driving"},{"id":"2106.05966","title":"Learning by Watching","created":"2021-06-10","cited_by_count":22,"area":"driving"},{"id":"2109.12516","title":"Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Driving","created":"2021-09-26","cited_by_count":22,"area":"driving"},{"id":"2207.00788","title":"Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles","created":"2022-07-02","cited_by_count":22,"area":"driving"},{"id":"2204.05513","title":"End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent","created":"2022-04-12","cited_by_count":21,"area":"driving"},{"id":"2502.16804","title":"Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advances","created":"2025-02-24","cited_by_count":21,"area":"driving"}],"next_cursor":"100"}