The platooning of trucks can be considered to be a potential approach to mitigate some of the negative effects that trucking can have on traffic streams. This paper proposes a cooperative distributed approach for forming/modifying platoons of trucks based on consensus algorithms. In this approach, trucks exchange information about their current status in real time, and the platoon is formed in consecutive iterations. This distributed consensus-based algorithm is compared with a centralized optimization-based algorithm for truck platooning, in which the trucks move with a set of predetermined speeds for a definite amount of time to form a platoon. The two approaches are tested and compared using various scenarios generated based on real data collected on a highway in Basel, Switzerland. Based on the results, the consensus-based algorithm proved to be a more general scheme that is able to form platoons even in cases with large initial separation of trucks. This algorithm is able to handle complex situations using its capability to form partial platoons.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Consensus-Based Algorithm for Truck Platooning


    Contributors:


    Publication date :

    2017-02-01


    Size :

    1151231 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    A Consensus-Based Algorithm for Truck Platooning

    Saeednia, Mahnam | Online Contents | 2017


    Truck Platooning Application

    Ellwanger, Simon / Wohlfarth, Enrico | British Library Conference Proceedings | 2017


    Truck Platooning Worldwide

    Atasayar, Hatun / Blass, Philipp / Kaiser, Susanne | Springer Verlag | 2022

    Free access

    Truck platooning application

    Ellwanger, S. / Wohlfarth, E. | IEEE | 2017


    Multidisciplinary Investigation of Truck Platooning

    Schnepf, Bastian / Kehrer, Christian / Maeurer, Christoph | SAE Technical Papers | 2020