Abstract

Abstract Background Variable message signs (VMS) have been widely applied to alleviate traffic congestion by providing spatiotemporal information related to traffic and network conditions to drivers. There is a debate on whether the VMS information would lead to the less-alleviation of congestion or congestion transfer to the adjacent roads in the different traffic congestion situations due to the inappropriate VMS information. Additionally, it is still unknown how to find a practically applicable method to design the most effective VMS information for drivers. Objective In order to design and display the appropriate VMS information for drivers under different traffic conditions, this paper aims to identify the effects of VMS on individuals’ route choice behavior by exploring the different effects of VMS on the several separate groups. Drivers in these groups are homogenous in gender, driving experience, education level, occupation, and monthly income. Methods In the hypothetical scenario, a stated preference (SP) questionnaire was conducted to build the dataset consisting of 3462 samples from local private and taxi drivers. The decision tree via the chi-squared automatic interactive detector (CHAID) algorithm is utilized to split drivers into several groups, and further two fixed-parameter logistic regression models considering intra-heterogeneity between drivers (i.e., considering and not considering systematic taste variations), and random-parameter logistic regression models are employed to analyze the factors affecting driver route choice behavior of each group. Results Five groups with different driver characteristics are identified. Besides, the modeling results indicate that the effect of the VMS information on individual route choice behavior is heterogeneous. These findings include: (i) random-parameter logistic regression models have a significantly improved goodness-of-fit because of the lower AIC and BIC; (ii) compared with the stated cause information on road construction and congestion, the accident information had a larger effect on driver route choice behaviors; (iii) the route choice behaviors of drivers with more than 6-year driving experience are affected by the VMS information on road constructions, accidents, and the quantitative delay time; (V) the route choice behaviors of less-experienced female drivers were affected by display formats and display frequencies of VMS information. Conclusions The findings from this study can assist traffic authorities in designing the most appropriate VMS for different traffic congestions based on driver characteristic distribution and the road capacity for improving the practicability of VMS information and further provide the theoretical evidence for the design of in-vehicle personalized information service systems.

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