scholarly journals Dynamical Analysis for Travel Behaviour and Travel Demand Prediction. Dynamic analysis of the route choice behavior considering the effect of traffic information.

1993 ◽  
pp. 77-86 ◽  
Author(s):  
Yasunori IIDA ◽  
Takashi UCHIDA ◽  
Nobuhiro UNO
2011 ◽  
Vol 97-98 ◽  
pp. 925-930
Author(s):  
Shi Xu Liu ◽  
Hong Zhi Guan

The influence of different traffic information on drivers’ day-to-day route choice behavior based on microscopic simulation is investigated. Firstly, it is assumed that drivers select routes in terms of drivers’ perceived travel time on routes. Consequently, the route choice model is developed. Then, updating the drivers’ perceived travel time on routes is modeled in three kinds of traffic information conditions respectively, which no information, releasing historical information and releasing predictive information. Finally, by setting a simple road network with two parallel paths, the drivers’ day-to-day route choice is simulated. The statistical characteristics of drivers’ behavior are computed. Considering user equilibrium as a yardstick, the effects of three kinds of traffic information are compared. The results show that the impacts of traffic information on drivers are related to the random level of driver’s route choice and reliance on the information. In addition, the road network cannot reach user equilibrium in three kinds of information. This research results can provide a useful reference for the application of traffic information system.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaowei Jiang ◽  
Yanjie Ji ◽  
Muqing Du ◽  
Wei Deng

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.


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