One of the pivotal challenges presented to urban road traffic controllers is the effective utilisation of transport infrastructure, as a result of growing urbanisation, the finite network capacity, and of the increasing number of road vehicles. The arrival of connected autonomous vehicles (CAVs) represents a unique opportunity for a fundamental change in urban mobility, and urban traffic control should take an active role in integrating CAVs into the mobility ecosystem in order to maximise benefits. A practical way to exploit CAVs for urban traffic control is to build an intelligent control mechanism that can distribute traffic in the controlled region. In this context, automated planning, a well-studied Artificial Intelligence topic, can provide techniques to dynamically generate plans to distribute traffic -thus maximising the network utilisation and reduce congestion. In this paper, we present an approach based on hybrid discrete continuous planning, and we demonstrate its impact using real-world historical data of a large UK town.


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    Title :

    A Hybrid Automated Planning Approach for Urban Real-time Routing of Connected Vehicles


    Contributors:


    Publication date :

    2021-09-19


    Size :

    441682 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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