This paper studied on the travel choice behavior with traffic state information that describe the degree of crowdedness based on the Expected Utility Theory and Bayesian Reasoning, and put forward the model to calculate the choice behavior with the traffic state information. Firstly, the analysis on the travel choice behavior with travel information as well as that without travel information was made based on the researches of CHORUS et al. Due to travelers face two types of uncertainty when choosing from and executing travel alternatives that are uncertainty of choice and uncertainty of execution. His update in perception based on the information received results in a decrease in levels of uncertainty he faces. There are two kinds of functions of the traffic information in decreasing the uncertainty of travel: On the one hand, the unknown choice could be known; on the other hand, the known choice could be elaborated. Secondly, Bayesian updating was then applied to represent the effect of the travel information and the models of travel choice with traffic state information were established. At last, the calculating process and value of traffic information were systematically introduced by an example. The research results indicate that the method of this paper puts forward a new method for analyzing and predicting the travel choice behavior with traffic state information that make up the shortcoming of models in existence, which can't describe the utility of traffic information. It is also useful for the study on effects of the travel information.


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    Title :

    The Travel Choice Behavior with Traffic State Information


    Contributors:
    Wu, Su-feng (author) / Yun, Mei-ping (author) / Yang, Xiao-guang (author) / Yang, Yang (author) / Lao, Yun-teng (author)

    Conference:

    First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China



    Publication date :

    2007-07-09




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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