Autonomous Driving Safety Evaluation

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14 papers in the last four weeks, up 75% on the four weeks before. 0.1% of all new papers.

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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
DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Models
Jun 15, 2026Xinglong Sun, Kevin Xie, Jenny Schmalfuss +5VLMs for Autonomous Driving Autonomous Driving Safety Evaluation
NVIDIA · KE:SAI
Is Your Trajectory Displacement Safe in Long-tail?
Jun 15, 2026Qiao Sun, Weicheng Zheng, Yixin Huang +1Autonomous Driving Safety Evaluation Autonomous Driving
Shanghai Qi Zhi Institute · Tongji University · Tsinghua University
When and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs
Jun 12, 2026Abhinaw Priyadershi, Jelena FrtunikjVLMs for Autonomous Driving Language Model Safety Evaluation
NVIDIA Corporation, Santa Clara, CA, USA · NVIDIA GmbH, Munich, Germany
Task-Aligned Stability Analysis of Vision-Language Models for Autonomous Driving Hazard Detection
Jun 10, 2026Everett RichardsVLM Evaluation VLM Robustness
Department of Computer Science, San Diego State University.
Mission-Level Runtime Assurance Framework for Autonomous Driving
Jun 5, 2026Chieh Tsai, Salim HaririAutonomous Driving Safety Evaluation Autonomous Driving Planning
Department of Electrical and Computer Engineering · The University of Arizona · Tucson, Arizona, USA
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
Risk Assessment of Autonomous Driving: Integrating Technical Failures, Ethical Dilemmas, and Policy Frameworks
Jun 4, 2026Boyi Chen, Shengqin Chu, Zicheng Wang +2Autonomous Driving Safety Evaluation Autonomous Driving
Faculty of Engineering, McMaster University
Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety
Jun 3, 2026Abhinaw Priyadershi, Mandar Pitale, Jelena Frtunikj +1AI Assurance Autonomous Driving Safety Evaluation
NVIDIA Corporation, Santa Clara, CA, USA · NVIDIA GmbH, Munich, Germany
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
What to Test Next: Interpretable Coverage Gap Discovery in Driving VLMs
Jun 1, 2026Abhishek Aich, Sparsh Garg, Vijay Kumar BG +2VLM Evaluation VLMs for Autonomous Driving
NEC Laboratories, America, USA · University of California, San Diego, USA
Safe2Drive: Evaluating Safe Driving Behaviors of E2E Autonomous Driving Models
May 29, 2026Nishad Sahu, Kalpana Panda, Congyuan Yu +3Autonomous Driving Benchmarks End-to-End Autonomous Driving
1Carnegie Mellon University · 2Birla Institute of Technology and Science Pilani
ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving
May 27, 2026Mohammadreza Teymoorianfard, Jean-Philippe Monteuuis, Jonathan Petit +1VLMs for Autonomous Driving Autonomous Driving Safety Evaluation
University of Massachusetts Amherst · Qualcomm
Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs
May 20, 2026Abhinaw Priyadershi, Jelena FrtunikjVLM Robustness VLMs for Autonomous Driving
NVIDIA Corporation, USA · NVIDIA GmbH, Germany
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
Reinterpreting Safety Thresholds as Neuron Spiking Thresholds
May 18, 2026Enrico Del Re, Mohamed Sabry, Cristina Olaverri-MonrealAutonomous Driving Safety Evaluation Autonomous Driving
Johannes Kepler University Linz, Austria; Department Intelligent Transport Systems
Multi-Agent Reinforcement Learning for Safe Autonomous Driving Under Pedestrian Behavioral Uncertainty
May 18, 2026Prakash Aryan, Kaushik Raghupathruni, Timo Kehrer +1Pedestrian Behavior Modeling Human Behavior Simulation
University of Bern, Bern, Switzerland. · AI4I, The Italian Institute of Artificial Intelligence, Turin, Italy.
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
Is VLA Reasoning Faithful? Probing Safety of Chain-of-Causation in Autonomous Driving Models
May 17, 2026Nicanor Mayumu, Xiaoheng Deng, Patrick MukalaCoT Faithfulness VLMs for Autonomous Driving
School of Computer Science and Engineering Central South University 932 Lushan Road, Changsha, Hunan P. R. China · School of Computer Science University of Wollongong in Dubai UOWD Building, Dubai Knowledge Park Dubai, United Arab Emirates
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
DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarios
May 16, 2026Sainithin Artham, Shankar Gangisetty, Avijit Dasgupta +1VLMs for Autonomous Driving Autonomous Driving Safety Evaluation
IIIT-Hyderabad, India
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
Belief-Space Residual Risk for Automated Driving under Localization Uncertainty
May 12, 2026Nijinshan Karunainayagam, Nils Gehrke, Frank DiermeyerUncertainty Quantification Autonomous Driving Safety Evaluation
Institute of Automotive Technology at the Technical University of Munich (TUM), DE-85748 Garching, Germany.
C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving
May 11, 2026Kefei Tian, Yuansheng Lian, Kai Yang +2VLM Robustness Counterfactual Evaluation of VLMs
College of Transportation, Tongji University, Shanghai, China · Department of Civil Engineering, Tsinghua University, Beijing 100084, China · School of Vehicle and Mobility, Tsinghua University, Beijing, China +1
HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving
May 11, 2026Zhongyu Xia, Guanyu Zhu, Guo Tang +2Autonomous Driving Benchmarks End-to-End Autonomous Driving
Wangxuan Institute of Computer Technology, Peking University
Practical validation of synthetic pre-crash scenarios
May 6, 2026Jian Wu, Ulrich Sander, Carol Flannagan +1Autonomous Driving Safety Evaluation Autonomous Driving Simulation
Safety Center, Volvo Cars, 41878 Göteborg, Sweden · Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 41756 Göteborg, Sweden · University of Michigan Transportation Research Institute, Ann Arbor, Michigan 48109, USA
Real-Time Evaluation of Autonomous Systems under Adversarial Attacks
May 5, 2026Adithya Mohan, Xujun Xie, Venkatesh Thirugnana Sambandham +1Autonomous Driving Safety Evaluation Adversarial Robustness
AI Motion Institute, Technische Hochschule Ingolstadt, Germany
Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive
Apr 30, 2026Yiru Wang, Anqing Jiang, Shuo Wang +4Autonomous Driving Benchmarks Autonomous Driving Safety Evaluation
Bosch Corporate Research, Bosch (China) Investment Ltd., Shanghai, China

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SPHINX: First Explain, Then Explore

Nguyen Do, Tue M. Cao, Tien Van Do, András Hajdu+2

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

Autonomous Driving Safety Evaluation Adversarial Robustness Adversarial Scenario Generation Autonomous Driving Simulation Autonomous Driving Scenario Generation

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Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent approaches rely primarily on the prior knowledge of Large Language Models and Vision-Language Models to generate driving scenarios procedurally. We argue that adversarial scenes should be generated based on the failure diagnosis (e.g., indecisiveness, multi-frame inconsistency) of the driving policy to specifically address the policy's weaknesses instead of relying on prior assumptions. In this paper, we propose SPHINX, a closed-loop framework for adversarial scenario synthesis guided by a simple principle: first explain, then explore. Beyond blindly exploring the scenario space, SPHINX leverages explainable artificial intelligence methods to analyze the policy, identifying key visual concepts and their influence on policy outputs, and the uncertainty of the decisions. Given the interpretable evidence extracted from the policy's own decision process, we use a vision language model to rationalize and criticize failure modes of the current policy. These critics are then used to generate targeted adversarial scenarios for policy retraining and improvement. We demonstrate that SPHINX can highlight an interpretable account of policy failures while other adversarial scene generation cannot. Across the evaluated benchmarks and test suites, SPHINX can be applied to diverse state-of-the-art autonomous vehicle architectures and yields consistent robustness improvements over existing scenario-generation methods.

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