This paper addresses a general stochastic user equilibrium (SUE) traffic assignment problem (TAP) for transport networks with electric vehicles (EV), where EV paths are restricted by the EV driving range limits. A minimization model for path-constrained SUE is first proposed as an extension of path-constrained deterministic user equilibrium (DUE) TAP, which also extends the existing general SUE models with link-based constraints to path-based constraints. The resulting SUE model and solution algorithm can be used for other conditions with similar path-based constraints. The equilibrium conditions reveal that any path cost in the network is the sum of corresponding link costs and a path specific out-of-range penalty term, while path out-of-range term should equal to zero to ensure feasible flows. We develop a modified method of successive averages (MSA) with a predetermined step size sequence where both multinomial logit and multinomial probit based loading procedure are applied to solve the TAP. The suggested methods incorporate K-shortest paths algorithm to generate the path set on a need basis. Finally, two numerical examples are presented to verify the proposed model and solution algorithms. © 2017 The Author(s).


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    Title :

    Stochastic traffic assignment of mixed electric vehicle and gasoline vehicle flow with path distance constraints



    Publication date :

    2017-01-01


    Remarks:

    Jing , W , Kim , I , Ramezani , M & Liu , Z 2017 , Stochastic traffic assignment of mixed electric vehicle and gasoline vehicle flow with path distance constraints . in S Lee & J Kim (eds) , International Symposia of Transport Simulation (ISTS) and the International Workshop on Traffic Data Collection and its Standardization (IWTDCS) : 7 - 8 July 2016, Jeju City, South Korea . Transport Research Procedia , vol. 21 , Elsevier , pp. 65-78 , International Symposium of Transport Simulation 2016 , Jeju , Korea, South , 23/06/16 . https://doi.org/10.1016/j.trpro.2017.03.078



    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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