In this paper, we aim to implement an urban network-level traffic routing scheme for autonomous vehicles to mitigate congestion in urban areas. We first present an implementation of a region-based dynamic traffic model. Subsequently, we present an innovative predictive routing approach for autonomous vehicles, dynamic forecast routing, and apply it on a set of homogeneous regions, making use of Urban-scale Macroscopic Fundamental Diagram to define the state of congestion in each region. This approach is compared with periodically adjusted routing, as well as logit routing, which is used to model self-interested human driver behavior. We also integrate a public transit diversion mechanism on all approaches. Results show that our approach surpasses all other approaches on all performance metrics by at least 40%.


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    Title :

    Region-based dynamic forecast routing for autonomous vehicles


    Contributors:


    Publication date :

    2016-11-01


    Size :

    496280 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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