Highlights Formulating a combinatorial optimization problem for dedicated bus lane (DBL) allocation. Integrating dynamic characteristics of congestion in the DBL problem. Proposing a learning process to estimate link potential for hosting DBL. Developing a Large Neighborhood Search with various types of destroy and repair methods. Testing the methods and algorithms in a simulation of a large-scale network.

    Abstract Dedicated bus lanes provide a low cost and easily implementable strategy to improve transit service by minimizing congestion-related delays. Identifying the best spatial distribution of bus-only lanes in order to maximize traffic performance of an urban network while balancing the trade-off between bus priority and regular traffic disturbance is a challenging task. This paper studies the problem of optimal dedicated bus lane allocation and proposes a modeling framework based on a link-level dynamic traffic modeling paradigm, which is compatible with the dynamic characteristics of congestion propagation that can be correlated with bus lane relative positions. The problem is formulated as a non-linear combinatorial optimization problem with binary variables. An algorithmic scheme based on a problem-specific heuristic and Large Neighborhood Search metaheuristic, potentially combined with a network decomposition technique and a performance-based learning process for increased efficiency, is proposed for deriving good quality solutions for large-scale network instances. Numerical application results for a real city center demonstrate the efficiency of the proposed framework in finding effective bus lane network configurations; when compared to the initial network state they exhibit the potential of bus lanes to improve travel time for car and bus users.


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    Titel :

    Modeling and optimization of dedicated bus lanes space allocation in large networks with dynamic congestion


    Beteiligte:


    Erscheinungsdatum :

    2021-03-03




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch