Influence of smartphone traffic application information on drivers' route choice behaviours

被引:2
|
作者
Qi, Xinyi [1 ]
Ji, Yanjie [1 ,2 ,3 ,4 ]
Yu, Jiajie [1 ]
Bu, Qing [5 ]
Samal, Dmitry Ivanovich [6 ]
机构
[1] Southeast Univ, Sch Transportat, Dongnandaxue Rd 2, Nanjing 210096, Peoples R China
[2] Jiangsu Key Lab Urban ITS, Nanjing, Peoples R China
[3] Jiangsu Prov Collaborat Innovat Ctr Modern Urban, Nanjing, Peoples R China
[4] Southeast Univ, Natl Demonstrat Ctr Expt Rd & Traff Engn Educ, Nanjing, Peoples R China
[5] Les Int Minsk Informat Technol Co Ltd, Minsk, BELARUS
[6] Belarusian State Univ Informat & Radioelect, Elect Comp Machines Dept, Minsk, BELARUS
基金
国家重点研发计划;
关键词
TRAVEL-TIME RELIABILITY; GENDER-DIFFERENCES; DECISION-MAKING; TOLL ROAD; MODEL; DIVERSION; IMPACT; CONGESTION; PREFERENCE; SYSTEM;
D O I
10.1049/itr2.12218
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The active traffic management system disseminates traffic information to drivers to guide their route choice, so as to alleviate traffic congestion. Most drivers are highly dependent on mobile navigation APP, and the display form of mobile navigation information is of great importance. In order to improve drivers' compliance with guidance information, this research accommodates for information that disseminate time attribute (when to provide the traffic information) and display format attribute (voice navigation or not, flat map or three-dimensional [3D] map) and also explores the interaction effects between individual and trip characteristics. A revealed preference (RP) and stated preference (SP) survey consisting of 831 respondents is conducted in Nanjing, China. Then three kinds of panel logit model are established to fit the survey data. According to the model results, it is found that drivers with aggressive style are more sensitive to travel time, and drivers who are familiar with the road network are more sensitive to the 3D map with voice navigation format. The results of parameter estimation are also used for the trade-off analysis of various exogenous variables. The findings of this study provide useful insights for the development of mobile navigation APPs, personalized path recommendation and congestion pricing strategies.
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页码:1413 / 1426
页数:14
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