Multiscale traffic flow modeling, which combines traffic models of different scales (e.g., of network and traffic representation), offers many opportunities for the simulation and evaluation of traffic measures and policies in large networks. For example, macroscopic continuum models of traffic flow could be used to simulate the propagation of traffic on large freeway corridors and networks efficiently and parsimoniously, whereas microscopic models of traffic flow could be used to simulate those parts of the network where more detail (e.g., lateral behavior) is required, such as at intersections and toll plazas. One key requirement of such a multiscale framework is related to the interface between models of different scales. This interface should ensure consistency in (a) vehicle conservation and (b) vehicle and traveler properties that must be transported over this interface (e.g., vehicle type, occupancy, and destination). In the approach presented, both types of consistency problems can be solved simultaneously, and this approach is illustrated with an integrated example. This multiscale modeling framework enables the coupling of any macroscopic model with any microscopic model (and vice versa) without putting constraints on the internal structure or parameterization in either model.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multiscale Traffic Flow Modeling in Mixed Networks


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2014-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    A Multiscale Symbolic Dynamic Entropy Analysis of Traffic Flow

    Zhanyou Cui / Gaoli Chen / Bing Liu et al. | DOAJ | 2022

    Free access

    Traffic Light Scheduling for Pedestrian-Vehicle Mixed-Flow Networks

    Zhang, Yi / Gao, Kaizhou / Zhang, Yicheng et al. | IEEE | 2019


    General modeling method for mixed traffic flow vehicle following behavior

    ZHANG JIAN / WANG XINKE | European Patent Office | 2024

    Free access

    A Spatiotemporal Multiscale Graph Convolutional Network for Traffic Flow Prediction

    Cao, Shuqin / Wu, Libing / Zhang, Rui et al. | IEEE | 2024


    Modeling Concepts for Mixed Traffic

    Schönauer, Robert / Stubenschrott, Martin / Huang, Weinan et al. | Transportation Research Record | 2012