By processing a large dataset composed of daily trajectories of thousands of students in Singapore, we find that, instead of simply picking up students from their homes, an optimal school shuttle planning system needs to learn the real transportation usage and plan across all potential pickup locations for every student to generate need-satisfying routes. It is challenging, however, to perform route planning over a large number of students each having multiple potential pickup locations. We develop a graph-based data structure that embeds potential pickup locations of all students with the awareness of real-world constraints and existing public transits. Based on the graph structure, we prove that the optimal last-mile school shuttle planning problem is NP-hard and thereafter design a Tabu-based expansion algorithm to solve the problem, which strikes at a proper balance between the savings of students’ commute time and the total cost of operating the shuttle buses. Extensive experiments with large-scale real-world crowdsensed trajectory data demonstrate that our last-mile school shuttles can save the traveling time for most students by over 20% and the savings can be up to 65% for 10% of the students.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Last-Mile School Shuttle Planning With Crowdsensed Student Trajectories


    Contributors:
    Tong, Panrong (author) / Du, Wan (author) / Li, Mo (author) / Huang, Jianqiang (author) / Wang, Wenqiang (author) / Qin, Zheng (author)


    Publication date :

    2021-01-01


    Size :

    4577324 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    FOLDING LAST-MILE MOBILITY

    JANG HYEON SUK / LEE YOON GEOL / LEE SEOL YOUNG et al. | European Patent Office | 2023

    Free access

    Last mile delivery system

    SALTER STUART C / WAAG ANDR ¨ / DAVID BRIAN GLICKMAN et al. | European Patent Office | 2024

    Free access

    FOLDING LAST-MILE MOBILITY

    JANG HYEON SUK / LEE YOON GEOL / LEE DONG PYO et al. | European Patent Office | 2024

    Free access

    LAST MILE DELIVERY SYSTEM

    SALTER STUART C / WAGH ARNAV / GLICKMAN DAVID BRIAN et al. | European Patent Office | 2024

    Free access