T2NBS: Planning Night-Time Demand-Oriented Bus Systems with Urban Computing Approaches
ID:1685 View Protection:ATTENDEE Updated Time:2021-12-03 13:43:49 Hits:197 Poster Presentation

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Abstract
This paper has established an urban computing framework T2NBS (Taxi to Night-time Bus Service) in order to realize the optimal NBS (Night-time Bus Service) system. The framework includes 1) a reasonable mathematical model MNL for travel demand estimation and a multi-variable decision target MINLP for the optimal system output, which simultaneously optimize the NBS system’s design quality (site, path, schedule, vehicle-to-passenger matching) and service quality (walking accessibility, demand-matching degree, travel time and travel cost, the profit of the whole system); 2) a staged sequential heuristic algorithm for solving the programming model’s “super integrated NP-Hard” problem, including the sub-algorithm for mining the night-time collective travel demands from taxi trajectories at the first stage, , the second-stage deployment sub-algorithm for extracting the fewest sites with best walking accessibility, and the third-stage sub-algorithm for searching the best operation timetable with maximized revenues.
Keywords
CICTP
Speaker
Qu Lei
School of Highway, Chang’an University

Submission Author
Qu Lei School of Highway, Chang’an University
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  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
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