{"total":106,"rows":[{"id":"2306.16927","title":"End-to-end Autonomous Driving: Challenges and Frontiers","created":"2023-06-29","cited_by_count":490,"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":"2312.03031","title":"Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?","created":"2023-12-05","cited_by_count":242,"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":"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":"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":"2503.07656","title":"DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving","created":"2025-03-07","cited_by_count":126,"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":"2306.07957","title":"Hidden Biases of End-to-End Driving Models","created":"2023-06-13","cited_by_count":96,"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":"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":"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":"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":"2305.04412","title":"Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors","created":"2023-05-08","cited_by_count":36,"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":"2412.09602","title":"Hidden Biases of End-to-End Driving Datasets","created":"2024-12-12","cited_by_count":30,"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":"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":"2309.10443","title":"Rethinking Imitation-based Planner for Autonomous Driving","created":"2023-09-19","cited_by_count":25,"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":"2506.23982","title":"StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving","created":"2025-06-30","cited_by_count":21,"area":"driving"},{"id":"2404.09496","title":"Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System","created":"2024-04-15","cited_by_count":20,"area":"driving"},{"id":"2401.10314","title":"LangProp: A code optimization framework using Large Language Models applied to driving","created":"2024-01-18","cited_by_count":18,"area":"driving"},{"id":"2503.02911","title":"Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test","created":"2025-03-04","cited_by_count":18,"area":"driving"},{"id":"2311.10747","title":"Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving","created":"2023-10-31","cited_by_count":17,"area":"driving"},{"id":"2403.02877","title":"ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving","created":"2024-03-05","cited_by_count":16,"area":"driving"},{"id":"2506.00034","title":"GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving","created":"2025-05-27","cited_by_count":16,"area":"driving"},{"id":"2510.24108","title":"Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer","created":"2025-10-28","cited_by_count":16,"area":"driving"},{"id":"2404.04869","title":"Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs","created":"2024-04-07","cited_by_count":13,"area":"driving"},{"id":"2405.19687","title":"Autonomous Driving with Spiking Neural Networks","created":"2024-05-30","cited_by_count":13,"area":"driving"},{"id":"2503.08162","title":"FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback","created":"2025-03-11","cited_by_count":12,"area":"driving"},{"id":"2508.09158","title":"EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Driving","created":"2025-08-05","cited_by_count":12,"area":"driving"},{"id":"2403.01238","title":"On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving","created":"2024-03-02","cited_by_count":10,"area":"driving"},{"id":"2412.02689","title":"Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving","created":"2024-12-03","cited_by_count":10,"area":"driving"},{"id":"2511.06253","title":"AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving","created":"2025-11-09","cited_by_count":10,"area":"driving"},{"id":"2503.03957","title":"Enhancing Autonomous Driving Safety with Collision Scenario Integration","created":"2025-03-05","cited_by_count":9,"area":"driving"},{"id":"2505.19516","title":"DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policy","created":"2025-05-26","cited_by_count":9,"area":"driving"},{"id":"2602.13301","title":"DriveMamba: Task-Centric Scalable State Space Model for Efficient End-to-End Autonomous Driving","created":"2026-02-09","cited_by_count":9,"area":"driving"},{"id":"2305.03303","title":"Occupancy Prediction-Guided Neural Planner for Autonomous Driving","created":"2023-05-05","cited_by_count":8,"area":"driving"},{"id":"2511.07292","title":"PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving","created":"2025-11-10","cited_by_count":8,"area":"driving"},{"id":"2403.12176","title":"Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving","created":"2024-03-18","cited_by_count":7,"area":"driving"},{"id":"2403.12552","title":"M2DA: Multi-Modal Fusion Transformer Incorporating Driver Attention for Autonomous Driving","created":"2024-03-19","cited_by_count":7,"area":"driving"},{"id":"2407.06546","title":"Exploring the Causality of End-to-End Autonomous Driving","created":"2024-07-09","cited_by_count":7,"area":"driving"},{"id":"2305.19904","title":"Efficient Learning of Urban Driving Policies Using Bird's-Eye-View State Representations","created":"2023-05-31","cited_by_count":6,"area":"driving"},{"id":"2402.12666","title":"Pre-trained Transformer-Enabled Strategies with Human-Guided Fine-Tuning for End-to-end Navigation of Autonomous Vehicles","created":"2024-02-20","cited_by_count":6,"area":"driving"},{"id":"2504.12667","title":"Fully Unified Motion Planning for End-to-End Autonomous Driving","created":"2025-04-17","cited_by_count":6,"area":"driving"},{"id":"2405.00316","title":"Enhance Planning with Physics-informed Safety Controller for End-to-end Autonomous Driving","created":"2024-05-01","cited_by_count":5,"area":"driving"},{"id":"2507.05754","title":"LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving","created":"2025-07-08","cited_by_count":5,"area":"driving"},{"id":"2508.07686","title":"Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning","created":"2025-08-11","cited_by_count":5,"area":"driving"},{"id":"2509.23922","title":"DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation","created":"2025-09-28","cited_by_count":5,"area":"driving"},{"id":"2305.18510","title":"RLAD: Reinforcement Learning from Pixels for Autonomous Driving in Urban Environments","created":"2023-05-29","cited_by_count":4,"area":"driving"},{"id":"2508.18898","title":"Interpretable Decision-Making for End-to-End Autonomous Driving","created":"2025-08-26","cited_by_count":4,"area":"driving"},{"id":"2511.13306","title":"DAP: A Discrete-token Autoregressive Planner for Autonomous Driving","created":"2025-11-17","cited_by_count":4,"area":"driving"},{"id":"2405.07573","title":"MaskFuser: Masked Fusion of Joint Multi-Modal Tokenization for End-to-End Autonomous Driving","created":"2024-05-13","cited_by_count":3,"area":"driving"},{"id":"2408.10908","title":"Enhancing End-to-End Autonomous Driving Systems Through Synchronized Human Behavior Data","created":"2024-08-20","cited_by_count":3,"area":"driving"},{"id":"2603.25968","title":"Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control","created":"2026-03-26","cited_by_count":3,"area":"driving"},{"id":"2605.18059","title":"Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations","created":"2026-05-18","cited_by_count":3,"area":"driving"},{"id":"2303.11888","title":"Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving","created":"2023-03-21","cited_by_count":2,"area":"driving"},{"id":"2308.01180","title":"Interpretable End-to-End Driving Model for Implicit Scene Understanding","created":"2023-08-02","cited_by_count":2,"area":"driving"},{"id":"2308.01496","title":"Target-point Attention Transformer: A novel trajectory predict network for end-to-end autonomous driving","created":"2023-08-03","cited_by_count":2,"area":"driving"},{"id":"2309.07808","title":"What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving","created":"2023-09-14","cited_by_count":2,"area":"driving"},{"id":"2312.06670","title":"Combating the effects of speed and delays in end-to-end self-driving","created":"2023-12-06","cited_by_count":2,"area":"driving"},{"id":"2409.01178","title":"Integrating End-to-End and Modular Driving Approaches for Online Corner Case Detection in Autonomous Driving","created":"2024-09-02","cited_by_count":2,"area":"driving"},{"id":"2409.12667","title":"METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance","created":"2024-09-19","cited_by_count":2,"area":"driving"},{"id":"2507.15266","title":"VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving","created":"2025-07-21","cited_by_count":2,"area":"driving"},{"id":"2603.14354","title":"Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces","created":"2026-03-15","cited_by_count":2,"area":"driving"},{"id":"2603.25672","title":"Can Users Specify Driving Speed? Bench2Drive-Speed: Benchmark and Baselines for Desired-Speed Conditioned Autonomous Driving","created":"2026-03-26","cited_by_count":2,"area":"driving"},{"id":"2210.06758","title":"Exploring Contextual Representation and Multi-Modality for End-to-End Autonomous Driving","created":"2022-10-13","cited_by_count":1,"area":"driving"},{"id":"2304.08252","title":"PaaS: Planning as a Service for reactive driving in CARLA Leaderboard","created":"2023-04-17","cited_by_count":1,"area":"driving"},{"id":"2309.00249","title":"Suicidal Pedestrian: Generation of Safety-Critical Scenarios for Autonomous Vehicles","created":"2023-09-01","cited_by_count":1,"area":"driving"},{"id":"2405.11995","title":"Compositionally Safe Construction of Autonomous Driving Systems","created":"2024-05-20","cited_by_count":1,"area":"driving"},{"id":"2411.17253","title":"LHPF: Look back the History and Plan for the Future in Autonomous Driving","created":"2024-11-26","cited_by_count":1,"area":"driving"},{"id":"2504.06584","title":"CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving","created":"2025-04-09","cited_by_count":1,"area":"driving"},{"id":"2509.13926","title":"MAP: End-to-End Autonomous Driving with Map-Assisted Planning","created":"2025-09-17","cited_by_count":1,"area":"driving"},{"id":"2509.22379","title":"A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systems","created":"2025-09-26","cited_by_count":1,"area":"driving"},{"id":"2511.09032","title":"Argus: Resilience-Oriented Safety Assurance Framework for End-to-End ADSs","created":"2025-11-12","cited_by_count":1,"area":"driving"},{"id":"2602.18757","title":"Driving Like Yourself: A Benchmark for Closed-Loop Personalized End-to-End Autonomous Driving","created":"2026-02-21","cited_by_count":1,"area":"driving"},{"id":"2604.03497","title":"Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving","created":"2026-04-03","cited_by_count":1,"area":"driving"},{"id":"2604.11854","title":"MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving","created":"2026-04-13","cited_by_count":1,"area":"driving"},{"id":"2605.12625","title":"Driving Intents Amplify Planning-Oriented Reinforcement Learning","created":"2026-05-12","cited_by_count":1,"area":"driving"},{"id":"2402.05064","title":"Tuning the feedback controller gains is a simple way to improve autonomous driving performance","created":"2024-02-07","cited_by_count":0,"area":"driving"},{"id":"2407.02878","title":"Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving","created":"2024-07-03","cited_by_count":0,"area":"driving"},{"id":"2502.09170","title":"LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancement","created":"2025-02-13","cited_by_count":0,"area":"driving"},{"id":"2503.07020","title":"Driving Through Uncertainty: Risk-Averse Control with LLM Commonsense for Autonomous Driving under Perception Deficits","created":"2025-03-10","cited_by_count":0,"area":"driving"},{"id":"2503.11062","title":"Active Learning from Scene Embeddings for End-to-End Autonomous Driving","created":"2025-03-14","cited_by_count":0,"area":"driving"},{"id":"2506.23995","title":"STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems","created":"2025-06-30","cited_by_count":0,"area":"driving"},{"id":"2507.23042","title":"Goal-Based Vision-Language Driving","created":"2025-07-30","cited_by_count":0,"area":"driving"},{"id":"2508.16962","title":"LLM-based Human-like Traffic Simulation for Self-driving Tests","created":"2025-08-23","cited_by_count":0,"area":"driving"},{"id":"2508.20762","title":"SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer","created":"2025-08-28","cited_by_count":0,"area":"driving"},{"id":"2509.22754","title":"Benchmarking Autonomous Driving Planners Across Leaderboards: A Unified CARLA-Based Evaluation","created":"2025-09-26","cited_by_count":0,"area":"driving"},{"id":"2510.08571","title":"Scalable Offline Metrics for Autonomous Driving","created":"2025-10-09","cited_by_count":0,"area":"driving"},{"id":"2602.10160","title":"AD$^2$: Analysis and Detection of Adversarial Threats in Visual Perception for End-to-End Autonomous Driving Systems","created":"2026-02-10","cited_by_count":0,"area":"driving"},{"id":"2606.01277","title":"DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidance","created":"2026-05-31","cited_by_count":0,"area":"driving"},{"id":"2606.10856","title":"An Exposure-Time-Aligned Primary-Path Architecture for Autonomous-Driving ECUs","created":"2026-06-09","cited_by_count":0,"area":"driving"}],"next_cursor":"100"}