诱导信息条件下驾驶路径选择行为分析  

Behavior analysis of driving route selection under condition of inducible information

作　　者：陈秀锋 陈伟 CHEN Xiufeng;CHEN Wei(School of Mechanical and Automotive Engineering,Qingdao University of Technology,Qingdao 266525,China)

机构地区：[1]青岛理工大学机械与汽车工程学院,山东青岛266525

出　　处：《现代电子技术》2022年第1期132-135,共4页Modern Electronics Technique

基　　金：国家自然科学基金项目(51678320);山东省自然科学基金项目(ZR2019MG012);山东省重点研发计划(2019GGX101038)。

摘　　要：为探究诱导信息对驾驶路径选择行为的影响及其作用机理,设计了SP调查问卷获取诱导信息下驾驶路径选择行为数据,应用SPSS软件对多元影响因子进行关键因子筛选以及影响特性分析,并基于二项Logit模型建立了诱导条件下驾驶路径选择行为模型。分析结果表明:驾龄、路网熟悉程度、诱导信息时效性是影响驾驶路径选择的关键因子,驾龄在2~5年的驾驶员变更路径的几率更大;对路网熟悉、认可可变信息实时性的驾驶员更倾向于变更路径,且路网熟悉程度、可变信息板时效性的影响表现为单调性。研究结果有利于构建诱导信息发布机制,提高诱导效率,为交通管理者制定诱导策略提供建议。In order to explore the influence of inducible information on driving route selection behavior and its action mechanism,an SP(stated preference) survey questionnaire is designed to obtain the driving route selection behavior data according to the inducible information,the SPSS software is used to screen the key factors of multiple influencing factors and analyze the influence characteristics,and the driving route selection behavior model under the condition of inducible information is established based on the binomial Logit model. The analysis results show that the drivers ′ driving years,familiarity for road network and timeliness of inducible information are the key factors which affect the choice of driving routes,and the drivers with the driving experience of 2~5 years are more likely to change their routes;drivers who are familiar with road network and can recognize the real-time characteristics of variable information are more inclined to change their routes,and the influence of drivers′ familiarity for road network and timeliness of variable message signs(VMS) is monotonous. It can be seen that the research is conducive to establish the mechanism of inducible information release and improve the inducible efficiency,and can provide suggestions for traffic managers to formulate inducible strategies.

关 键 词：驾驶路径选择 诱导信息 出行路径 SP调查 行为模型 驾驶特性 诱导效率 城市交通 

分 类 号：TN919.5-34[电子电信—通信与信息系统] U491[电子电信—信息与通信工程]