Manchester Metropolitan University's Research Repository

    Next Road Rerouting: A Multi-Agent System for Mitigating Unexpected Urban Traffic Congestion

    Wang, Shen, Djahel, Soufiene ORCID logoORCID: https://orcid.org/0000-0002-1286-7037, Zhang, Zonghua and McManis, Jennifer (2016) Next Road Rerouting: A Multi-Agent System for Mitigating Unexpected Urban Traffic Congestion. IEEE Transactions on Intelligent Transportation Systems, 17 (10). pp. 2888-2899. ISSN 1524-9050

    Accepted Version
    Download (3MB) | Preview


    During peak hours in urban areas, unpredictable traffic congestion caused by en-route events (e.g. vehicle crashes) increases drivers’ travel time and, more seriously, decreases their travel time reliability. In this paper, an original and highly practical vehicle re-routing system called Next Road Rerouting (NRR) is proposed to aid drivers in making the most appropriate next road choice so as to avoid unexpected congestions. In particular, this heuristic rerouting decision is made upon a cost function which takes into account the driver’s destination and local traffic conditions. In addition, the newly designed Multi-Agent System (MAS) architecture of NRR allows the positive rerouting impacts on local traffic to be disseminated to a larger area through the natural traffic flow propagation within connected local areas. The simulation results based on both synthetic and realistic urban scenarios demonstrate that, compared to the existing solutions, NRR can achieve a lower average travel time while guaranteeing a higher travel time reliability in the face of unexpected congestion. The impacts of NRR on the travel time of both rerouted and non-rerouted vehicles are also assessed and the corresponding results reveal its higher practicability.

    Impact and Reach


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics for this dataset are available via IRStats2.


    Repository staff only

    Edit record Edit record