Binary Probit Model on Drivers Route Choice Behaviors Based on Multiple Factors Analysis

Abstract

This study explores many details of the drivers response to dynamic travel information with variable message signs (VMS) which is the one of the most common advanced traveler information systems (ATIS) deployed in many areas all over the world. A stated preference (SP) survey was conducted to collect various drivers route choice behavior with VMS. Based on the surveys, seventeen potential affecting factors such as city kind, region, gender, age, marital status, degree, job, whether full-time worker, monthly income, crowded level on the current route, vehicle queue length of the current route, delay ratio of the current route, knowledge of an alternate route, length ratio of an alternate route, crowded level on an alternate route, anticipated travel time saving ratio and quality of dynamic travel information were identified and applied to further study. A binary probit model was adopted to evaluate the significance of these seventeen factors. Gender, age, whether full-time worker, delay ratio of the current route, knowledge of an alternate route, length ratio of an alternate route, and crowded level on an alternate route were proved to be significant variables. Then a model for estimating drivers route choice results was build based on the significant variables. The verification results showed that the model estimating precision could reached 76 %.

This paper is supported by Training Program of the Major Research Plan of National Police University of China (Study on Road Traffic State Extraction based on Locating Point Group of GPS Equipped Vehicles), General Project of Liaoning Provincial Education Department of China (L2015554), Technology Research Program of Ministry of Public Security of China (Study on Road Traffic State Extraction based on Locating Point Group of GPS Equipped Vehicles) and Project of Natural Science Foundation of Liaoning Province (Dual-mode Traffic Guidance Models and Information Releasing policies).