Lees M N, Lee J D
Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA, USA.
Ergonomics. 2007 Aug;50(8):1264-86. doi: 10.1080/00140130701318749.
Automotive collision warning systems (CWS) can enhance hazard identification and management. However, false alarms (FAs), which occur as a random activation of the system not corresponding to a threat and not interpretable by the driver, and unnecessary alarms (UAs), which occur in situations judged hazardous by the algorithm but not by the driver, may limit CWS effectiveness. A driving simulator was used to investigate the influence of CWS (accurate, UA, FA, none) and distraction on driver performance during non-critical and critical events. FAs and UAs differentially influenced trust and compliance. FAs diminished trust and compliance, whereas the context associated with UAs fostered trust and compliance during subsequent events. This study suggests current warning descriptions based on signal detection theory need to be expanded to represent how different types of alarms affect drivers.
汽车碰撞预警系统（CWS）可以增强危险识别和管理能力。然而，误报（FAs），即系统随机激活但并非对应实际威胁且驾驶员无法理解的情况，以及不必要警报（UAs），即在算法判定为危险但驾驶员不认为危险的情况下出现的警报，可能会限制CWS的有效性。使用驾驶模拟器来研究CWS（准确、不必要警报、误报、无）以及分心对非关键和关键事件期间驾驶员表现的影响。误报和不必要警报对信任和依从性有不同影响。误报会降低信任和依从性，而与不必要警报相关的情境在后续事件中会增强信任和依从性。本研究表明，基于信号检测理论的当前警报描述需要扩展，以体现不同类型警报对驾驶员的影响。
