Dynamic lane assignment (DLA) is an effective method to improve traffic flow and optimize urban road resources. However, lane switching can disrupt traffic under dynamic control due to clearance time and driving characteristics. Traditional rule-based methods hinder the selection of optimal schemes for DLA systems. On-site data analysis shows that lane switching increases saturated headway by 18.4% and reduces lane group utilization by 17.8% compared to fixed lanes in the same direction. To address these challenges, this study proposes an optimization method that integrates DLA and signal timing, considering the impact of lane switching. The proposed model aims to minimize total delay at intersections by optimizing the number and timing of lane switches within a given interval. Case studies and extensive numerical analyses demonstrate that the proposed method outperforms the rule-based approach, reducing total intersection delay by 1.91%. Additionally, the average number of lane switches decreases by 13.8%, reducing safety risks associated with frequent lane switching. Sensitivity analysis reveals the superiority of the proposed method when the utilization rate of variable lanes is below 0.4 and the saturated headway caused by lane switching exceeds 2.9 seconds. Moreover, the proposed method outperforms inductive and adaptive control schemes when the traffic flow deviation coefficient is less than 0.3. This makes it suitable for implementation in cities where drivers have limited experience with variable lanes during the initial stage, when historical and real-time data are more consistent. Overall, the proposed method offers significant improvements in traffic flow efficiency and safety in DLA systems.


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    Titel :

    Dynamic Lane Assignment and Signal-Timing Collaborative Optimization Considering the Effect of Lane Switching


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Wang, Jiawen (Autor:in) / Feng, Yang (Autor:in) / Zhao, Jing (Autor:in) / Zhang, Cheng (Autor:in) / Chen, Yanxin (Autor:in)


    Erscheinungsdatum :

    2024-03-03




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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