Autonomous Driving Scenario Generation

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8 papers in the last four weeks, up 60% on the four weeks before. 0.1% of all new papers.

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Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records
Jun 30, 2026Anjali Parashar, Chuchu FanAutonomous Driving Safety Evaluation Synthetic Data Generation
Massachusetts Institute of Technology, Cambridge, MA
InfiniVerse: Occupancy Guided Unbounded Scene Generation for Autonomous Driving
Jun 30, 2026Xiaoyu Ye, Leheng Li, Xinyu Ji +8Long-Horizon Video Generation 3D Scene Generation
The Chinese University of Hong Kong, Shenzhen · The Hong Kong University of Science and Technolody(Guangzhou) · Nanyang Technological University +2
TrafficAlign: Aligning Large Language Models for Traffic Scenario Generation
Jun 27, 2026Zhi Tu, Liangkun Niu, Tianyi ZhangLLM Alignment Autonomous Driving Safety Evaluation
Purdue University
Proposal-Conditioned Latent Diffusion for Closed-Loop Traffic Scenario Generation
Jun 25, 2026Shubham Vaijanath Phoolari, Aleyna Kara, Christoph Lauer +1Diffusion Guidance Diffusion Model Acceleration
Authors are with CARIAD SE, Germany. · Author is with the Institute of Automotive Engineering (FZD), TU Darmstadt, Germany. · Author is with the Technical University of Munich, Germany.
From Driving Videos to Simulatable Scenarios
Jun 20, 2026Alexandre Levy, Ernest Valveny Llobet, Antonio Manuel LópezAutonomous Driving Simulation Autonomous Driving Scenario Generation
Dept. Computer Science, Universitat Aut`onoma de Barcelona (UAB) · Computer Vision Center (CVC), UAB
FrozenDrive: Zero-Shot Text-Guided Driving Scene Generation and Data Augmentation with Parameter-Free Frozen Diffusion Model
Jun 18, 2026Yuhwan Jeong, Hyeonseong Kim, Daehyun We +5Synthetic Data Augmentation Video Diffusion Models
KAIST, Visual Intelligence Lab
SPHINX: First Explain, Then Explore
Jun 16, 2026Nguyen Do, Tue M. Cao, Tien Van Do +3Autonomous Driving Safety Evaluation Adversarial Robustness
University of Florida, Gainesville, Florida, USA · Budapest University of Technology and Economics, Department of Networked Systems and Services, Budapest, Hungary · University of Debrecen, Debrecen, Hungary
ControlMap: Controllable High-Definition Map Generation for Traffic Scenario Simulation
Jun 14, 2026Marwan Farag, Steffen Wäldele, Yu YaoHD Map Construction Procedural Content Generation
University of Stuttgart, Stuttgart, Germany · Robert Bosch GmbH, Renningen, Germany · Motional, Inc
CausalDrive: Real-time Causal World Models for Autonomous Driving
Jun 13, 2026Tianyi Yan, Huan Zheng, Dubing Chen +10Action-Conditioned Video Generation Autonomous Driving
SKL-IOTSC, CIS, University of Macau · Xiaomi EV · CASIA
From Attacks to Curricula: Learnability-Guided Adversarial Training for Safe Autonomous Driving
Jun 12, 2026Yuewen Mei, Tong Nie, Jie Sun +3Adversarial Training Autonomous Driving
College of Transportation & Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, 201804, China · Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
Dash2Sim: Closed-Loop Driving Simulation from in-the-wild Dashcam Videos
Jun 5, 2026Anurag Ghosh, Francesco Pittaluga, Khiem Vuong +4Autonomous Driving Datasets Autonomous Driving Benchmarks
1Carnegie Mellon University · 2NEC Labs America · 3MIT∗ +1
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Jun 4, 2026Qi Lan, Yining Tang, Yu Shen +4Flow Matching Autonomous Driving Safety Evaluation
College of Mechanical and Vehicle Engineering Chongqing University, Chongqing, China
EvoDrive: Pareto Evolution for Safety-Critical Autonomous Driving via Self-Improving LLM Agents
Jun 2, 2026Tong Nie, Yuewen Mei, Yihong Tang +4Multi-Objective Evolutionary Optimization Autonomous Driving Safety Evaluation
The Hong Kong Polytechnic University · Tongji University · McGill University +1
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation
Jun 2, 2026Aarti Basant, Amlan Kar, Despoina Paschalidou +30Action-Conditioned Video Generation Video Diffusion Models
NVIDIA
PairedGTA: Generating Driving Datasets for Controlled Photometric Shift Analysis
May 31, 2026Andrea Chianese, Giulio Rossolini, Alessandro Biondi +2Autonomous Driving Datasets Autonomous Driving Perception
Scuola Superiore Sant’Anna, Pisa, Italy, Department of Excellence in Robotics & AI · University of Pisa, DII, Pisa, Italy
CityGen: Structure-Guided City-Style Synthesis for Cross-City Autonomous Driving
May 28, 2026Zezhong Qian, Zhao Yang, Lu Tan +4Domain Adaptation Conditional Image Generation
1Jiangsu Cytoderm Intelligent Technology Co., Ltd., China · 2Xi’an Jiaotong University, Xi’an, China · 3Tsinghua University, Beijing, China +1
AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond
May 25, 2026Haiming Zhang, Junfei Zhou, Feng Jiang +6Long-Horizon Video Generation 3D Scene Generation
Li Auto · Southwest Jiaotong University · Tsinghua University
Physics-Aware 3D Gaussian Editing for Driving Scene Generation
May 25, 2026Feng Zhou, Jian Zhang, Yuhang Sun +53D Gaussian Splatting 3D Scene Editing
School of Artificial Intelligence, Jilin University, Changchun, China. · China FAW Group Co., Ltd., Changchun, China. · National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China.
ARCANE-PedSynth: Synthetic Multi-Pedestrian Datasets with Behavioural Crossing Annotations
May 24, 2026Muhammad Naveed Riaz, Maciej Wielgosz, Antonio M. López PeñaAutonomous Driving Datasets Pedestrian Behavior Modeling
Departament de Ciències de la Computació and Computer Vision Center (CVC), Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain · Institute of Electronics, Faculty of Computer Science, Electronics and Telecommunications, AGH University of Krakow, Kraków, Poland
ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving
May 20, 2026Qiyu Ruan, Yuxuan Wang, He Li +2Autonomous Driving Safety Evaluation Adversarial Scenario Generation
State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC), University of Macau, Macau, China · Faculty of Science and Technology, University of Macau, Macau, China
Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic
May 18, 2026Lorenzo Bonin, Francesco Giacomarra, Luca Bortolussi +2Autonomous Driving Safety Evaluation Synthetic Data Generation for Robotics
University of Trieste · University of Southern California
Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving
May 18, 2026Lijun Zhou, Hongcheng Luo, Zhenxin Zhu +34Dynamic Scene Reconstruction World Models for Autonomous Driving
Xiaomi Auto World Model Team
Scenario Generation in Roundabouts with Adjustable Interaction Intensity
May 18, 2026Li Li, Till Temmen, Tobias Brinkmann +3Autonomous Driving Simulation Automated Test Generation
Chair of Mechatronics in Mobile Propulsion, RWTH Aachen University, Germany
KG-ASG: Collision-Knowledge-Guided Closed-Loop Adversarial Scenario Generation With Primary-Support Attribution
May 17, 2026Cheng Wang, Chen Xiong, Ziwen Wang +2Autonomous Driving Safety Evaluation Adversarial Scenario Generation
Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions
May 17, 2026Qingwen Pu, Kun Xie, Yuan Zhu +1Human Behavior Simulation Autonomous Driving Safety Evaluation
Transportation Informatics Lab, Department of Civil and Environmental Engineering, Old Dominion University, Norfolk, VA 23529, United States · Inner Mongolia Center for Transportation Research, Inner Mongolia University, Rm A357A, Transportation Building, Inner Mongolia University South Campus, 49 S Xilin Rd, Hohhot, Inner Mongolia, 010020, China · School of Transportation and Logistics, National Engineering Laboratory of Integrated Transportation Big Data Application Technology, National and Local Joint Engineering Research Center of Integrated Transportation Intelligence, Southwest Jiaotong University, Chengdu 611756, China
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment
May 15, 2026Chuancheng Zhang, Zhenhao Wang, Kaizheng Li +3Autonomous Driving Safety Evaluation Synthetic Data Generation
Shenzhen Research Institute of Shandong University, Shenzhen, 518057, Guangdong, China · School of Airspace Science and Engineering, Shandong University, 264209 Weihai, China. · School of Computer Science and Technology, Shandong University of Finance and Economics, 250014, Jinan, China.
Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles
May 13, 2026Yizhuo Xiao, Haotian Yan, Ying Wang +5AI Accountability Autonomous Driving Safety Evaluation
School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K. · State Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai, China · College of Computer Science and Technology, Jilin University, Changchun, China +3
Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
May 13, 2026Kaicong Huang, Talha Azfar, Weisong Shi +13D Gaussian Splatting Synthetic Data Generation
Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY USA 12180. · Department of Computer and Information Sciences, University of Delaware, Newark, DE USA 19716.
SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics
May 8, 2026Yicheng Zhu, Yang Chen, Tao Li +1GPU Acceleration Vehicle Dynamics
Rochester Institute of Technology · City University of Hong Kong
Traffic Scenario Orchestration from Language via Constraint Satisfaction
May 7, 2026Frieda Rong, Chris Zhang, Kelvin Wong +1Autonomous Driving Simulation Automated Test Generation
University of Toronto · 2Waabi

Jun 30, 2026, cs.AIJ/K move · Enter open · S save

Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records

Anjali Parashar, Chuchu Fan

Massachusetts Institute of Technology, Cambridge, MA

Autonomous Driving Safety Evaluation Synthetic Data Generation Autonomous Driving Simulation Automated Test Generation Autonomous Driving Scenario Generation

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To ensure safe on-road behavior, pre-deployment testing and failure discovery of Autonomous Driving Systems (ADS) is crucial. Present day simulation based testing methods focus largely on mathematical models for efficient search of optimal scenarios, assuming a fixed scenario representation. On the other hand, real-world testing involves substantial manual effort to design scenario templates for testing. These templates represent distinct failure scenarios consisting of pre-deployment vehicle movements, map types, etc. Historical failure records for ADS are a reliable source of real-world failure conditions, which can be used for scenario generation. In this work, we propose a scenario generation pipeline using categorical and contextual information available from historical records in natural language format. Our approach consists of modular LLM based synthetic scenario generation, compatible with the testing constraints of a given system. We successfully apply our method to generate a diverse set of scenarios for testing autonomous navigation on Metadrive simulator using the NHTSA ADS crash records. Our approach results in accurate and diverse scenario generation with a combination of 4 road types, 3 non ego vehicle movement types, including on road anomalies in the form of working zones. Generated scenarios align with the provided testing conditions, and reveals interesting failures of the system within a limited testing budget of 20 scenarios. Code is available at https://github.com/anjaliParashar/crash2scenario.

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