CAERI(SH:601965) Zhong Guo Qi Che Bao Wang·2025-06-30 02:14Core Viewpoint - The development of intelligent connected vehicles in China is facing significant challenges in safety assessment and standard formulation, particularly due to the black-box nature of AI models and the safety issues related to edge cases [1][2]. Group 1: Challenges in Intelligent Driving Assessment - The primary challenge in intelligent driving assessment is the black-box characteristic of AI models and the safety long-tail problem associated with edge scenarios [1]. - Traditional testing methods are insufficient for the complex dynamic processes involved in driving, especially for rare edge cases that could lead to system failures [1]. Group 2: Recommendations for Improvement - There is a need to innovate testing and evaluation methods, combining road tests, experimental tests, and simulation tests to enhance efficiency and accuracy [2]. - Accelerating the formulation of national and industry standards, particularly for AI products, is essential for guiding healthy industry development [2]. Group 3: Current Deficiencies and Future Improvements - The rapid development of intelligent driving products has outpaced the establishment of relevant standards and testing methods [2]. - Future improvements should focus on accelerating the development of standards, innovating testing methods for edge scenarios, establishing comprehensive testing scenario libraries, and enhancing international cooperation [2]. Group 4: Successful Cases and Industry Insights - The China Automotive Engineering Research Institute has developed the iVISTA intelligent vehicle index evaluation system, which assesses intelligent vehicles across multiple dimensions [3]. - This system has gained industry recognition and supports the establishment of intelligent driving standards and certifications [3]. Group 5: Impact of Testing Technology on Development - Testing technology plays a crucial role in the research and application of intelligent driving functions, ensuring safety and enhancing user experience [4]. - Effective testing methods can help identify product issues and provide improvement suggestions, fostering continuous product optimization [4]. Group 6: Additional Considerations in Assessment - Beyond technical aspects, safety, ethics, and user experience are critical factors in the assessment of intelligent driving systems [6]. - A qualified intelligent vehicle must meet standards in safety, user experience, and ethical considerations to avoid disrupting traffic order and causing dissatisfaction among other road users [6].