CO-Mode with AV-CRM: A novel paradigm towards human–machine collaboration in intelligent vehicle safety - Jiayi Lu; Bin Sun; Boao Zhang; Zhaowen Pang; Zhaoxia Peng; Shichun Yang; Yaoguang Cao (Journal of Safety Science and Resilience)
With the continuous advancement in vehicle intelligence, enhancing safety has emerged as a key priority in intelligent vehicle research and development. Intelligent vehicles are currently limited in supporting autonomous or human-driven modes. This limitation becomes apparent in complex driving scenarios, where vehicle risk response capabilities are inadequate. This paper suggests that shifting from a single decision maker to a human–machine collaboration approach is a potential solution. However, current research on human–machine collaboration in intelligent vehicles primarily focuses on intelligent systems that assist the driver, rather than treating the driver and the system as equals. This approach overlooks the role of the driver in helping the system, lacks effective communication, and diminishes the sense of collaborative cooperation, all of which hinder the promotion of efficient, safe, and stable driving. Inspired by the aviation approach to risk management through Crew Resource Management (CRM), this study introduces the Collaborative Operation Mode (CO-Mode) for intelligent vehicles. Based on CO-Mode’s requirements for human–machine collaborative perception, decision making, and control, the Autonomous Vehicle Collaborative Resource Management (AV-CRM) is proposed. In addition, challenges and future perspectives are explored by analyzing the abilities and limitations of relevant technologies. The proposed AV-CRM redefines the relationship between drivers and intelligent systems, offering new insights into the safety of intelligent vehicles and their technological evolution.