This paper presents a modified paired combinatorial Logit route choice model that takes the advantages of both Probit and Logit models to produce more reasonable flow prediction with close-form probabilities that can be easily calculated. To better account for the observation error of the model, parameters are calculated basing that the variance of impendence is related to the measured travel time. The concept of stochastic equivalent impendence is proposed to calculate the utility of each route pair and Clark's approximation for normal distribution is used to compute the equivalent impendence. The proposed equivalence concept also eliminates the need of computing similarity index as shown in most modified Logit model. Two numerical tests on the well-known examples show that the proposed model is more close to Probit model than original PCL model with reasonable errors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Modified Paired Combinatorial Logit Route Choice Model with Probit-Based Equivalent Impedance


    Contributors:
    Li, Jun (author) / Lai, Xinjun (author) / Xie, Lianghui (author)

    Conference:

    Third International Conference on Transportation Engineering (ICTE) ; 2011 ; Chengdu, China


    Published in:

    ICTE 2011 ; 648-653


    Publication date :

    2011-07-13




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Solving the Overlapping Problem in Route Choice with Paired Combinatorial Logit Model

    Chen, Anthony / Kasikitwiwat, Panatda / Ji, Zhaowang | Transportation Research Record | 2003


    ADAPTATION OF THE PAIRED COMBINATORIAL LOGIT MODEL TO THE ROUTE CHOICE PROBLEM

    Pravinvongvuth, Surachet / Chen, Anthony | Taylor & Francis Verlag | 2005


    Combined multinomial logit modal split and paired combinatorial logit traffic assignment model

    Wang, Jian / Peeta, Srinivas / He, Xiaozheng et al. | Taylor & Francis Verlag | 2018