To address the problems of ramp merging, this paper proposes a multi-lane centralized merging strategy in mixed traffic flow. First, vehicles group into platoon blocks, with CAVs serving as the lead vehicle to guide the following HDVs to merge safely. Second, a hierarchical optimization framework is established. An OMS-DFST algorithm is proposed in the upper layer to dynamically search for the optimal merging sequence of platoon blocks. Based on the merging sequence derived from the upper layer, an optimal cooperative merging control method is presented in the lower layer to determine the optimal trajectory. By taking efficiency, fuel consumption, pollution emissions, and comfort as cost functions, the optimal control input is solved by applying the Pontryagin principle. Results indicate the proposed strategy can effectively improve efficiency and comfort, and compared to the traditional FIFO algorithm, the vehicle’s fuel consumption is reduced by 5.5%, and pollution emissions are decreased by 4.5%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Novel Tree Search-Based Ramp Merging Strategy in a Multi-Lane Mixed Traffic Flow


    Contributors:
    Li, Ze (author) / Wu, Xia (author) / Zhao, Xiangmo (author)

    Conference:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Published in:

    CICTP 2024 ; 1553-1562


    Publication date :

    2024-12-11




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Cooperative On-Ramp Merging Control Model for Mixed Traffic on Multi-Lane Freeways

    Hou, Kangning / Zheng, Fangfang / Liu, Xiaobo et al. | IEEE | 2023




    Dual-Layer Deep Reinforcement Learning for Lane Merging Control in On-Ramp Traffic

    Zhou, Tong / Huang, Yuzhao / Tian, Yudan et al. | ASCE | 2024


    Deep Multi-Agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic

    Chen, Dong / Hajidavalloo, Mohammad R. / Li, Zhaojian et al. | IEEE | 2023