A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Drivers’ diversion from expressway under real traffic condition information shown on variable message signs
Abstract To alleviate the traffic congestion on urban expressway, Variable Message Signs (VMS) have been widely employed for diverting some traffic to arterial streets in large cities. The diversion rate is a key parameter to design, operation and evaluation of the VMS. Many works have been done to study the diversion rate by stated preference survey. However, no consistent conclusion has been obtained on the key factors influencing diversion behavior. Therefore, this paper pays attention to analyzing the drivers’ diversion from expressway behavior under different network and traffic conditions, and finding the key factors influencing diversion behavior by using stated preference survey. In the survey, graphical traffic information is provided as scenario simulation. Ordinal regression method is adopted to explore the key factors influencing diversion willingness. Binary logit model is used to explore the divert decision with given traffic information. It is shown that driving years, income, driving style, average trip length, and degree of trust in VMS are the significant factors to diversion willingness. Furthermore, the same VMS displaying state results in different diversion flow at different sites. Those findings are the foundation to optimize traffic information releasing strategy and improve the road network efficiency.
Drivers’ diversion from expressway under real traffic condition information shown on variable message signs
Abstract To alleviate the traffic congestion on urban expressway, Variable Message Signs (VMS) have been widely employed for diverting some traffic to arterial streets in large cities. The diversion rate is a key parameter to design, operation and evaluation of the VMS. Many works have been done to study the diversion rate by stated preference survey. However, no consistent conclusion has been obtained on the key factors influencing diversion behavior. Therefore, this paper pays attention to analyzing the drivers’ diversion from expressway behavior under different network and traffic conditions, and finding the key factors influencing diversion behavior by using stated preference survey. In the survey, graphical traffic information is provided as scenario simulation. Ordinal regression method is adopted to explore the key factors influencing diversion willingness. Binary logit model is used to explore the divert decision with given traffic information. It is shown that driving years, income, driving style, average trip length, and degree of trust in VMS are the significant factors to diversion willingness. Furthermore, the same VMS displaying state results in different diversion flow at different sites. Those findings are the foundation to optimize traffic information releasing strategy and improve the road network efficiency.
Drivers’ diversion from expressway under real traffic condition information shown on variable message signs
Li, Xingang (author) / Cao, Yakang (author) / Zhao, Xiaomei (author) / Xie, Dongfan (author)
KSCE Journal of Civil Engineering ; 19 ; 2262-2270
2014-12-19
9 pages
Article (Journal)
Electronic Resource
English
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