Abstract: Drivers reaction times are an essential parameter to study driving behavior. There are many factors influencing drivers reaction times, but few studies have been conducted on the differences between these factors. Correctly judging the importance of each influencing factor is conducive to improve the forewarning distance model of any driver assistance system. Thirteen influential factors were chosen through analysis of drivers reaction times, including the drivers own factors, road conditions, and traffic environment. Based on a questionnaire survey, three criterion and thirteen indictors of the influential factor of drivers reaction times were prioritized using the analytic hierarchy process (AHP), and the weight vector of the importance was put forward. Among the criterion, drivers own factors possess the largest weight, the final weight of which was 0.637. Among the thirteen indicators, weather conditions have the largest weight, which was 0.252. Driving experience was subordinate to weather conditions, with a weight of 0.203. Through the driving stimulation platform, the research shows that the results are in agreement with the conclusions drawn by the AHP method.

Key words: traffic and transportation engineering, driving behavior, reaction time, analytic hierarchy process

摘要： 驾驶员反应时间是研究驾驶行为的1项重要参数，影响驾驶员反应时间的因素较多，各个因素之间存在差异性，正确判断各个影响因素的重要程度有助于完善辅助驾驶系统的预警距离模型。通过分析，选取了13个影响因素进行研究，这些影响因素主要通过驾驶员自身状况、道路状况以及环境状况3个方面影响驾驶员反应时间。通过问卷调查，利用AHP对影响因素的3个准则13个指标进行重要度排序。在准则层中，驾驶员自身状况的影响最大，其权重值为0.637；在指标层中，天气状况因素影响最大，其权重值为0.252；驾驶经验影响因素次之，其权重值为0.203。并通过驾驶模拟舱平台对影响因素重要度排序进行验证，结果与AHP法得出的结论相吻合。

关键词: 交通运输工程, 驾驶行为, 反应时间, 层次分析法