地下道路分合流区驾驶员视认行为研究  

Driver's Visual Recognition in Diverging and Merging Area of Underground Roads

作　　者：路记红 钟石泉[1] 马寿峰[1] 白子建[2] 周丽珍[1] 

机构地区：[1]天津大学管理与经济学部系统工程研究所,天津300072 [2]天津市市政工程设计研究院,天津300051

出　　处：《交通信息与安全》2013年第5期10-18,共9页Journal of Transport Information and Safety

基　　金：国家自然科学基金项目(批准号:50908155;71101102)资助

摘　　要：当前地下道路交通事故频发且严重程度高,而提高地下道路交通标志的视认性是缓解地下道路交通安全问题的重要的措施之一。采用问卷调查和模拟驾驶实验的方法进行数据收集,并量化可能影响驾驶员视认性的各种因素,采用SPSS进行多项Logistic回归,从而提取影响驾驶员对地下道路分流标志视认的关键因素。回归结果表明,驾驶员的自身因素和交通状况均对驾驶员的视认行为产生重要影响,且各因素的因素程度由高到低排序依次为:职业、年龄、前车距、车流量等。建立了可以估算驾驶员产生不同等级注意程度的概率的预测模型,从而有针对性的对驾驶员进行培训,进而提高交通运行的安全程度。Many serious traffic accidents have taken place at diverging/merging areas of underground roads,and therefore,it is important to improve the visibility of traffic signs.In this regard,this paper uses a questionnaire and driving simulator to collect data,quantifies relevant factors affecting visual recognition of drivers,and then extracts the key factors influencing driver's visual recognition to the diverging/merging signs of underground road segments through a multi-Logistic regression analysis within SPSS.The results show that personality traits and traffic conditions have an important impact on visual recognition,and the rank of these variables,based on a decreasing order of their importance,is occupation,age,gap distance,and vehicular flux.In addition,aprediction model is developed to estimate the probability for each attention level that a driver holds at aparticular time.The model can be used to develop a tailored training for each individual driver according to their own characteristics,which shall further improve traffic safety.

关 键 词：视认 分流标志 地下道路 LOGISTIC回归 

分 类 号：U458.1[建筑科学—桥梁与隧道工程]