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

Wang, Jing; Chang, Ande; LianXing, Gao

doi:10.1007/978-3-319-38789-5_30

Cited by 4 publications

(2 citation statements)

References 6 publications

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Section: Data Sourcesmentioning

confidence: 99%

“…RP survey can obtain the driver's real driving habits and preferences, as well as the actual response to traffic information on real road networks [17, 29]. The SP survey allows respondents to make choices by simulating real road scenes [21, 30, 31]. The RP survey cannot obtain the results of the driver's choice of new roads, so the influencing factors that can be investigated are limited, and the SP survey sometimes does not reflect the driver's response in the actual driving process.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2022

IET Intelligent Trans Sys

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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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