We explore the impact of travel information sharing on road networks using a two-layer, agent-based, day-to-day traffic network model. The first layer (cyber layer) represents a conceptual communication network where travel information is shared among drivers. The second layer (physical layer) captures the day-to-day evolution of a traffic network. Instead of having perfect information, the drivers are assumed to form groups, among which travel information is shared and utilized for routing decisions. The formation of groups occurs in the cyber layer according to the notion of percolation, which describes the formation of connected clusters in a random graph. The notion of percolation captures the disaggregated and distributed nature of travel information sharing. We present numerical studies on the convergence of the traffic network with a range of percolation rates. The findings suggest a positive correlation between the percolation rate and the speed of convergence, which is validated through statistical analysis.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Agent-based day-to-day traffic network model with information percolation


    Contributors:

    Published in:

    Publication date :

    2017-01-02


    Size :

    29 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Parallel Simulation of Agent-Based Model for Air Traffic Network

    Kim, Young Jin / Pinon-Fischer, Olivia J. / Mavris, Dimitri N. | AIAA | 2015


    Stochastic Percolation Network Model for Hybrid Nanocomposites

    Gbaguidi, Audrey / Namilae, Sirish / Kim, Daewon | IEEE | 2020




    An agent-based simulation model of traffic congestion

    Breen, J.M. / Jensen, P. / Marchal, F. | British Library Conference Proceedings | 2007