Autonomous Driving Simulation

Latest papers 215

25 papers in the last four weeks, up 79% on the four weeks before. 0.1% of all new papers.

FlowSim: Rendering-Free Closed-Loop Simulation for Evaluating End-to-End Driving Systems
Oct 13, 2026Hanfeng Wu, Alvaro Marcos-Ramiro, Michael Schmidt +1Autonomous Driving Simulation End-to-End Autonomous Driving
Karlsruhe Institute of Technology Munich, Germany · BMW Group Munich, Germany · Karlsruhe Institute of Technology Karlsruhe, Germany
Human Behavior-Informed Crash Scenario Generation with Real-World Crash Priors for Autonomous Vehicle Safety Evaluation
Oct 3, 2026Mingxing Peng, Xusen Guo, Long Chen +3Autonomous Driving Scenario Generation Autonomous Driving Safety Evaluation
The Hong Kong University of Science and Technology (Guangzhou), China · Institute of Automation Chinese Academy of Sciences, Beijing, China · The University of Hong Kong, Hong Kong, China +1
Retrieval-Augmented Large Language Model Decision-Making for Autonomous Driving Guided by Chinese Philosophical Wisdom
Oct 2, 2026Xiaojun Bi, Xiaoyuan Ma, Yiwen Sun +5Autonomous Driving LLM Decision-Making
Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, and School of Information and Engineering, Minzu University of China, Beijing 100081, China · Institute for Artificial Intelligence, Peking University, Beijing 100871, China · State Key Laboratory of General Artificial Intelligence, BIGAI, Beijing 100080, China +4
SceneFactory-3D: Lifting 2D Traffic Scenes into 3D Physical Counterfactuals for Scalable Physically Grounded Safety Evaluation
Oct 2, 2026Yicheng Zhu, Linfeng Tian, Tianmu Zhao +4Autonomous Driving Simulation Autonomous Driving Safety Evaluation
Rochester Institute of Technology · City University of Hong Kong · New York University
TerrainForge: Physics-Grounded Road Geometry Editing for Counterfactual Autonomous Driving
Oct 2, 2026Yang Chen, Yicheng Zhu, zhenning Li +2Autonomous Driving Scenario Generation Autonomous Driving Simulation
Rochester Institute of Technology · University of Macau · City University of Hong Kong
DyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes
Sep 30, 2026Merav Keidar, Tomer Borreda, Rajalakshmi Nandakumar +1Millimeter-Wave Radar mmWave Radar Sensing
Technion · Cornell Tech · NVIDIA
TrafficSignBench: Rule-Centric Closed-Loop Evaluation of Traffic-Sign Compliance in Autonomous Driving
Sep 29, 2026Victoria Smirnova, Viktoriia Zinkovich, Gregorii Bukhtuev +4Autonomous Driving Benchmarks Autonomous Driving Safety Evaluation
Lomonosov Moscow State University · FusionBrain Lab · Moscow Institute of Physics and Technology +3
Agent-Based Evolutionary Dynamics for Mixed Autonomy Weaving Ramps
Sep 29, 2026Sheryl Paul, Kexin Wang, Ruolin Li +1Intelligent Transportation Systems Agent-Based Modeling
University of Southern California, Los Angeles, CA, USA.
VehicleArena: A Realistic Urban Environment for Multi-Agent Driving
Sep 28, 2026Jie Yang, Jiajun Chen, Jiazheng Zhou +4Autonomous Driving Benchmarks Autonomous Driving
Fudan University · Shanghai Innovation Institute
SV2V-RSim: A Comprehensive Benchmark for Self-Selective V2V Cooperative Perception with Near-Realistic Data
Sep 26, 2026Yulu Wu, Chao Wei, Jujun Cheng +6Cooperative Perception Autonomous Driving Datasets
Tongji University, Shanghai, China · Anhui University, Hefei, China · University of Toyama, Toyama, Japan
OneFixer: High-Quality and Consistent One-Step Autoregressive 3DGS Refinement for Driving Scenes
Sep 26, 2026Boseong Jeon, Junhyeop Lee, Juhan Cha +1One-Step Generative Modeling Temporal Consistency in Video Generation
142dot · Hyundai Motor Company
Guiding End-to-End Driving Models with Endpoint-Constrained Trajectory Optimization
Sep 25, 2026Brayden Zhang, Mahsa Golchoubian, Igor Gilitschenski +2End-to-End Autonomous Driving Trajectory Optimization
University of Toronto · Vector Institute · NVIDIA Research +2
RECAST: From Log Replay to Closed-Loop Driving Simulation with View-Complete Actors
Sep 25, 2026Zijun Zhao, Liewen Liao, Kang Shen +2Autonomous Driving Simulation 3D Asset Generation
Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai 200240, China · School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, and the Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
DriveHierarchy: A Benchmark for Diagnosing VLM Driving Capabilities from Open-Loop Understanding to Closed-Loop Execution
Sep 25, 2026Chengkai Xu, Jiaqi Liu, Yicheng Guo +2Autonomous Driving Benchmarks VLMs for Autonomous Driving
College of Transportation, Tongji University, Shanghai, China · Department of Computer Science, UNC Chapel Hill, NC, USA
Timed Rule-Based Supervision of an End-to-End Autonomous Parking Policy
Sep 24, 2026Kejia Gao, Liguo Zhou, Lei Yu +1Autonomous Parking Runtime Assurance
Combining Evasive and Braking Reactions for Safety Reference Models in Automated Vehicles
Sep 24, 2026Riccardo Donà, Konstantinos Mattas, Biagio CiuffoCollision Avoidance Autonomous Driving Safety Evaluation
Joint Research Centre for the European Commission, Ispra, IT
HelloWorld: Towards Practical Applications of Generative Driving World Models
Sep 24, 2026Fan Lu, Hanshi Wang, Zijing Wang +20Multi-View Video Generation World Models for Autonomous Driving
Teach-to-Crash: A Closed-Loop Student-Teacher LLM Framework for Collision-Inducing Test Scenario Generation
Sep 23, 2026Zaid Ghazal, Khouloud Gaaloul, Bruce MaximAutonomous Driving Safety Evaluation Adversarial Scenario Generation
University of Michigan-Dearborn Dearborn, MI, USA
BranchDrive: A Branch-Structured Dataset for Action-Conditioned Driving Prediction
Sep 23, 2026Feeza Khan Khanzada, Sudarshan Sridhar, Jaerock KwonAutonomous Driving Datasets Autonomous Driving Benchmarks
Department of Electrical and Computer Engineering, University of Michigan-Dearborn, 4901 Evergreen Rd, Dearborn, MI 48128, United States
DreamStream: Towards Policy-Oriented Generative Simulation for End-to-End Driving
Sep 22, 2026Ziyang Leng, Sicheng Mo, Seth Z. Zhao +4Autonomous Driving Benchmarks End-to-End Autonomous Driving
University of California, Los Angeles · Toyota Research Institute
NavSafe- $\infty$ : Benchmarking Closed-Loop Driving Safety in Photorealistic Environments
Sep 22, 2026Yuxin Bao, Hongwei Ruan, Luobin Wang +7Autonomous Driving Benchmarks End-to-End Autonomous Driving
UCLA · UCSD · Toyota Research Institute
ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation
Sep 18, 2026Boni Hu, Xiong Wei, Haoming Huang +20World Models for Autonomous Driving Autonomous Driving Simulation
ZYT AI Team
Safety-Critical Scenarios Emerge from Initial Scenes
Sep 17, 2026Yin Wu, Jiarong Wei, Carl Esselborn +4Adversarial Scenario Generation Autonomous Driving Simulation
REARL: A Closed-loop Autonomous Driving Simulation Enhancement Framework with Real Traffic Data and Large Language Models
Sep 17, 2026Xiaojun Bi, Jun Jiang, Yiwen Sun +6Language Model-Based Control Human Behavior Simulation
Minzu University of China, Beijing, China · Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, 100081, China · Peking University, Beijing, China +4
Imitation Learning for Autonomous Driving in CARLA
Sep 15, 2026Jordy KietoAutonomous Driving Imitation Learning
Geometry vs Structure: Graph-Based Diagnostics for LiDAR Point-Cloud Simulation Fidelity
Sep 14, 2026Ghazal Farhani, Taufiq RahmanDigital Twins Spectral Methods
Automotive and Surface Transportation Research Centre, National Research Council Canada, London, Ontario, Canada.
Comfort by Construction: Adaptive, Comfort-Bounded Action Spaces for Learned Driving Policies
Sep 11, 2026Anna Rothenhäusler, Daniel Jost, Raghu Rajan +4Constrained RL Vehicle Dynamics
University of Freiburg, Freiburg, Germany · Bosch Center for Artificial Intelligence, Stuttgart, Germany · Coburg University of Applied Sciences, Coburg, Germany
High-Fidelity Multi-Body Simulator for Autonomous Racing
Sep 11, 2026Nicola Musiu, Francesco Iacovacci, Fausto Lupo +11Autonomous Racing Vehicle Dynamics
University of Modena and Reggio Emilia, Modena, Italy · Megaride S.r.l., Naples, Italy · University of Naples Federico II, Naples, Italy +1
CARLAverse: A Highly Modular, Distributed, and Multimodal Framework for Human-in-the-Loop Simulation
Sep 10, 2026Patrick Rebling, Philipp Nenninger, Reiner KriestenHaptic Feedback Autonomous Driving Simulation
Institute of Energy Efficient Mobility Karlsruhe University of Applied Sciences
Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling
Sep 8, 2026Rx Fan, Z HanMulti-Agent Trajectory Prediction Multimodal Trajectory Prediction
School of Systems Science, Beijing Normal University

Oct 13, 2026J/K move · Enter open · S save

FlowSim: Rendering-Free Closed-Loop Simulation for Evaluating End-to-End Driving Systems

Hanfeng Wu, Alvaro Marcos-Ramiro, Michael Schmidt, Christoph Stiller

Karlsruhe Institute of Technology Munich, Germany · BMW Group Munich, Germany · Karlsruhe Institute of Technology Karlsruhe, Germany

Autonomous Driving Simulation End-to-End Autonomous Driving World Models for Autonomous Driving

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Closed-loop evaluation of end-to-end (E2E) driving systems typically relies on generating sensor observations and re-processing them through the perception encoder, introducing substantial computational cost and a sim2real gap between simulated and real sensor observations. In this paper, we ask a more fundamental question: is image-space simulation necessary for closed-loop evaluation of E2E driving systems? We propose FlowSim, a rendering-free simulation paradigm that predicts the internal latent representation directly from a previous latent and target-frame symbolic scene conditions. The predicted latent is then processed by the original frozen downstream modules, eliminating image rendering and perception re-encoding. Explicit cross-frame agent association improves latent transition prediction and rollout stability, while variable-horizon simulation enables long-horizon prediction from a common real anchor without accumulating intermediate rollout errors. Experiments on nuScenes and NavSim demonstrate that FlowSim preserves downstream behavior competitively with, and often exceeds image-space simulation in source-to-reference agreement across variable simulation horizons and both dense and sparse latent representations. By predicting the latent directly, both instantiations of FlowSim simulate each step in 0.04--0.06s, substantially faster than the image-space simulation methods they are compared against. These results establish FlowSim as an efficient and practical alternative to conventional image-space simulation methods.