With the recent development of autonomous vehicle technology, there have been active efforts on the deployment of this technology at different scales that include urban and highway driving. While many of the prototypes showcased have been shown to operate under specific cases, little effort has been made to better understand their shortcomings and generalizability to new areas. Distance, uptime and number of manual disengagements performed during autonomous driving provide a high-level idea on the performance of an autonomous system but without proper data normalization, testing location information, and the number of vehicles involved in testing, the disengagement reports alone do not fully encompass system performance and robustness. Thus, in this study a complete set of metrics are applied for benchmarking autonomous vehicle systems in a variety of scenarios that can be extended for comparison with human drivers and other autonomous vehicle systems. These metrics have been used to benchmark UC San Diego's autonomous vehicle platforms during early deployments for micro-transit and autonomous mail delivery applications.
Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework
National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University（汽车底盘集成与仿生国家重点实验室，吉林大学）；Department of Computer Science, Durham University（杜伦大学计算机科学系）；School of Engineering and Physical Sciences, Heriot-Watt University（赫瑞斯泰大学工程与物理科学学院）；DRIVEResearch
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
University of Tübingen（蒂宾根大学）；Tübingen AI Center（蒂宾根人工智能中心）；Robert Bosch GmbH（罗伯特·博世有限公司）；OpenDriveLab at Shanghai AI Lab（上海人工智能实验室OpenDriveLab）；NVIDIA Research（英伟达研究院）；Nanyang Technological University（南洋理工大学）；University of Toronto（多伦多大学）；Vector Institute（向量研究院）；Stanford University（斯坦福大学）
FLYINGTRUST: A Benchmark for Quadrotor Navigation Across Scenarios and Vehicles
School of Electronics and Communication Enginnering, Sun Yet-sen University, Shenzhen, China（电子与通信工程学院，孙逸森大学，深圳，中国）；Tianwei Xunda (Hunan) Technology Co., Ltd., Hunan, China（天威湘电（湖南）科技有限公司，湖南，中国）
AutoLay: Benchmarking amodal layout estimation for autonomous driving
Robotics Research Center, KCIS（KCIS机器人研究中心）；IIIT Hyderabad（海得拉巴国际信息技术学院）；Mila - Quebec AI Institute, Montreal（蒙特利尔魁北克人工智能研究所）；Université de Montréal（蒙特利尔大学）
University of Texas at Austin（德克萨斯大学奥斯汀分校）；University of California Berkeley（加州大学伯克利分校）；Harvard University（哈佛大学）；Delft University of Technology（代尔夫特理工大学）；Google Brain（谷歌大脑）
TaCarla: A comprehensive benchmarking dataset for end-to-end autonomous driving
Tuğrul Gorgülü *†（土耳其巴伊塞蒂大学）；Atakan Dağ †（土耳其巴伊塞蒂大学）；M. Esat Kalfaoğlu ‡（土耳其巴伊塞蒂大学）；Halil İbrahim Kuru †（土耳其巴伊塞蒂大学）；Barış Can Cam †（土耳其巴伊塞蒂大学）；Halil İbrahim Öztürk †（土耳其巴伊塞蒂大学）；Özsel Kılınç §（土耳其巴伊塞蒂大学）
Bench-RNR: Dataset for Benchmarking Repetitive and Non-repetitive Scanning LiDAR for Infrastructure-based Vehicle Localization
Shanghai Jiao Tong University（上海交通大学）；Key Laboratory of System Control and Information Processing, Ministry of Education of China（系统控制与信息处理教育部重点实验室）；Shanghai Engineering Research Center of Intelligent Control and Management（上海市智能控制与管理工程研究中心）；Global College, Shanghai Jiao Tong University（上海交通大学全球学院）
Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving
Donald Bren School of Information and Computer Sciences, University of California, Irvine（加州大学欧文分校唐纳德·布伦信息与计算机科学学院）；School of Computing, National University of Singapore（新加坡国立大学计算学院）；Nanyang Technological University（南洋理工大学）；Shanghai AI Laboratory（上海人工智能实验室）
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
Texas A&M University（德州农工大学）；University of Toronto（多伦多大学）；University of Wisconsin-Madison（威斯康星大学麦迪逊分校）；University of Maryland（马里兰大学）；University of Texas at Austin（德克萨斯大学奥斯汀分校）；UNC Chapel Hill（北卡罗来纳大学教堂山分校）
Benchmarking Empirical and Learning-Based Approaches for Feedforward Steering Control in Autonomous Racing
Chair of Automatic Control, Department of Engineering Physics and Computation, Technical University of Munich（慕尼黑技术大学自动控制系）；Professorship of Autonomous Vehicle Systems (AVS), Department of Mobility Systems Engineering, Technical University of Munich（慕尼黑技术大学移动系统工程系自动驾驶车辆系统教授职位）
Nigel -- Mechatronic Design and Robust Sim2Real Control of an Over-Actuated Autonomous Vehicle
Automation, Robotics and Mechatronics Laboratory (ARMLab), Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR)（自动化、机器人与机电实验室（ARMLab），汽车工程系，克莱姆森大学国际汽车研究中心（CU-ICAR））；Department of Mechanical Engineering, Clemson University（机械工程系，克莱姆森大学）
