Abstract Traffic flow mobility on expressway plays an important role in urban development. With the emergent technologies, connected vehicles, including both connected automated vehicles (CAVs) and connected regular vehicles (CRVs), are equipped with connectivity features to improve efficiency of urban expressway in a mixed traffic scenario. Existing research indicates that without targeted management, the integration of CAVs and CRVs into regular vehicles (RVs) traffic can lead to a series of congestion issues. A potential solution lies in the implementation of dedicated lanes, each designated for specific vehicle types, which could alleviate traffic flow complications. Therefore, this paper proposes a dynamic optimal lane management strategy for multi-lane mixed traffic urban expressway, aimed at maximizing the whole discharge flow. To begin with, we present an analytical method to mathematically derive discharge flow of each lane type including mixed traffic lane, CAV/CRV dedicated lane, and RV dedicated lane, from the perspective of both traffic demand and traffic capacity. Then, taking a three-lane mixed traffic urban expressway as an application, we conduct a numerical analysis of the dynamic optimal lane management strategy, based on comparisons among eight distinct strategies, under varying factors of traffic demands, penetration rates of CAVs and CRVs, and allocation proportions of vehicles upstream assigned to mixed traffic lanes. The results validate the effectiveness of the analytical method proposed for lane management strategies. It also indicates that the aforementioned system factors have significant impacts on the dynamic optimal lane management strategy.


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    Title :

    Dynamic optimal lane management strategy for multi-lane urban expressway with bi-class connected vehicles


    Contributors:
    Yanyan Qin (author) / Changqing Liu (author) / Lulu Xie (author) / Honghui Tang (author)


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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