Towards a Universal Evaluation Model for Careful and Competent Autonomous Driving
Kethan Reddy, Elias Nassif, Panagiotis Angeloudis, Mohammed Quddus, Washington Ochieng
备注：
arXiv admin comment: This version has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission
Virtual scenario-based testing methods to validate autonomous driving systems are predominantly centred around collision avoidance, and lack a comprehensive approach to evaluate optimal driving behaviour holistically. Furthermore, current validation approaches do not align with authorisation and monitoring requirements put forth by regulatory bodies. We address these validation gaps by outlining a universal evaluation framework that: incorporates the notion of careful and competent driving, unifies behavioural competencies and evaluation criteria, and is amenable at a scenario-specific and aggregate behaviour level. This framework can be leveraged to evaluate optimal driving in scenario-based testing, and for post-deployment monitoring to ensure continual compliance with regulation and safety standards.
Language-Driven Policy Distillation for Cooperative Driving in Multi-Agent Reinforcement Learning
Department of Computer Science at University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校计算机科学系）；College of Transportation and Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University（同济大学交通学院及交通工程教育部重点实验室）；Department of Mechanical Engineering at the University of California, Berkeley（加州大学伯克利分校机械工程系）
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving
Huawei Noah’s Ark Lab（华为诺亚方舟实验室）；Hong Kong University of Science and Technology（香港科技大学）；Huawei Intelligent Automotive Solution BU（华为智能汽车解决方案BU）；Sun Yat-sen University（中山大学）
RGB-Event Fusion for Moving Object Detection in Autonomous Driving
University of Burgundy (Université de Bourgogne)（勃艮第大学）；ETH Zurich（苏黎世联邦理工学院）；Univ Rouen Normandie（鲁昂诺曼底大学）；Université de Lorraine（洛林大学）；CNRS（法国国家科学研究中心）；Inria（法国国家信息与自动化研究所）
The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey
School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；Vehicle Safety Institute, Graz University of Technology（格拉茨技术大学车辆安全研究所）；State Key Laboratory of Automotive Simulation and Control, Jilin University（吉林大学汽车仿真与控制国家重点实验室）
DPGP: A Hybrid 2D-3D Dual Path Potential Ghost Probe Zone Prediction Framework for Safe Autonomous Driving
National Key Laboratory of General Artificial Intelligence, Key Laboratory of Machine Perception (MoE), School of Intelligence Science and Technology, Peking University（国家关键人工智能实验室、机器感知（MoE）重点实验室、智能科学与技术学院，北京大学）；PKU-WUHAN Institute for Artificial Intelligence（北京大学-武汉人工智能研究院）；School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）；School of Instrument Science and Engineering, Southeast University（东南大学仪器科学与工程学院）；China Automotive Innovation Corporation（中国汽车创新公司）
Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles
School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K.（1 工程与物理科学学院，赫瑞-沃顿大学，爱丁堡，英国）；State Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai, China（2 自主智能无人系统国家重点实验室，同济大学，上海，中国）；College of Computer Science and Technology, Jilin University, Changchun, China（3 计算机科学与技术学院，吉林大学，长春，中国）；University of Shanghai for Science and Technology, Shanghai, China（4 上海科技大学，上海，中国）；National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China（5 汽车底盘集成与生物力学国家重点实验室，吉林大学，长春，中国）；Department of Civil Engineering, The University of Hongkong, Hongkong, China（6 市政工程系，香港大学，香港，中国）
Adaptive Time Step Flow Matching for Autonomous Driving Motion Planning
HRI；Honda Research Institute（本田研究院）；Northeastern University（东北大学）；Princeton University（普林斯顿大学）；University of Maryland（马里兰大学）；Stanford University（斯坦福大学）
CooperRisk: A Driving Risk Quantification Pipeline with Multi-Agent Cooperative Perception and Prediction
UCLA Mobility Lab, University of California, Los Angeles, USA（加州大学洛杉矶分校移动实验室）；Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China（教育部道路与交通工程重点实验室）
