Vehicle trajectory data are essential in smart mobility applications, yet often incomplete, necessitating systematic reconstruction for effective use. Existing methods often overlook traffic rules and vehicle interactions in their reconstruction process, a research gap that becomes critical for fine-grained reconstruction of incomplete and irregular microscopic traffic data. To address this limitation, this paper introduces a novel fine-grained trajectory reconstruction (FTR) framework, particularly for urban signalized intersections, considering both traffic rules and vehicle interactions through a microscopic traffic simulation (MTS) model. This is motivated by challenging missing patterns in real-world data from Alibaba City Brain Lab and limitations in existing reconstruction approaches. To this end, the FTR problem is first formulated as an MTS-based optimization problem. Then, to solve this problem effectively under a limited computing budget, an advanced dynamic data-driven evolutionary optimization technique, D3GA++, is proposed. Through the validation involving two real-world datasets, D3GA++ has demonstrated superior performance under various missing data scenarios consistently surpassing baselines such as brute-force random search and standard evolutionary algorithm in terms of reconstruction accuracy. Our work can have crucial implications for traffic management, urban planning, and autonomous vehicle technology development.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fine-Grained Trajectory Reconstruction by Microscopic Traffic Simulation With Dynamic Data-Driven Evolutionary Optimization


    Contributors:
    Naing, Htet (author) / Cai, Wentong (author) / Yu, Jinqiang (author) / Zhong, Jinghui (author) / Yu, Liang (author)


    Publication date :

    2025-02-01


    Size :

    4251893 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Traffic state reconstruction method and system based on sparse microscopic vehicle trajectory data

    WANG XIANG / WU HAO / WANG YINBO et al. | European Patent Office | 2024

    Free access

    Dynamic Equilibrium Assignment with Microscopic Traffic Simulation

    Liu, H. X. / Ma, W. / Ban, J. X. et al. | British Library Conference Proceedings | 2005


    Dynamic equilibrium assignment with microscopic traffic simulation

    Liu, H.X. / Wenteng Ma, / Ban, J.X. et al. | IEEE | 2005


    Two-stage fine-grained vehicle trajectory generation method

    XIE JINMAN / GAO YANG / FENG ZUNLEI et al. | European Patent Office | 2023

    Free access