摘要
This study investigates drivers＇ diversion decision behavior under expressway variable message signs that provide travel time of both an expressway route and a local street route. Both a conventional cross-sectional logit model and a mixed logit model are developed to model drivers＇ response to travel time information. It is based on the data collected from a stated preference survey in Shanghai, China. The mixed logit model captures the heterogeneity in the value of ＂travel time＂ and ＂number of traffic lights＂ and accounts for correlations among repeated choices of the same respondent. Results show that travel time saving and driving experience serve as positive factors, while the number of traffic lights on the arterial road, expressway use frequency, being a middle-aged driver, and being a driver of an employer-provided car serve as negative factors in diversion. The mixed logit model obviously outperforms the cross-sectional model in dealing with repeated choices and capturing heterogeneity regarding the goodness-of-fit criterion. The significance of standard deviations of random coefficients for travel time and number of traffic lights evidences the existence of hetero- geneity in the driver population. The findings of this study have implications for future efforts in driver behaviormodeling and advanced traveler information system assessment.
This study investigates drivers＇ diversion decision behavior under expressway variable message signs that provide travel time of both an expressway route and a local street route. Both a conventional cross-sectional logit model and a mixed logit model are developed to model drivers＇ response to travel time information. It is based on the data collected from a stated preference survey in Shanghai, China. The mixed logit model captures the heterogeneity in the value of ＂travel time＂ and ＂number of traffic lights＂ and accounts for correlations among repeated choices of the same respondent. Results show that travel time saving and driving experience serve as positive factors, while the number of traffic lights on the arterial road, expressway use frequency, being a middle-aged driver, and being a driver of an employer-provided car serve as negative factors in diversion. The mixed logit model obviously outperforms the cross-sectional model in dealing with repeated choices and capturing heterogeneity regarding the goodness-of-fit criterion. The significance of standard deviations of random coefficients for travel time and number of traffic lights evidences the existence of hetero- geneity in the driver population. The findings of this study have implications for future efforts in driver behaviormodeling and advanced traveler information system assessment.
基金
supported by a project (No. 51008195) funded by National Natural Science Foundation of China
a Shanghai First-Class Academic Discipline Project (No. S1201YLXK) funded by Shanghai Government
a project (No. 14XSZ02) funded by University of Shanghai for Science and Technology
a project funded by Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University
