基于旅客出行需求数据的机场巴士站点布局与路径优化研究

doi:10.3976/j.issn.1002-4026.20240131

Abstract

Abstract: This study analyzed actual passenger travel demand based on city bus and subway card swipe data to provide data support for airport bus station selection and route optimization. First, travel demand centers were identified by analyzing card swipe data, and the K-medoids clustering algorithm was used to cluster city-wide travel demands. The resulting travel demand centers, along with major transportation hubs such as railway stations, were selected as shuttle bus stations to provide passengers with convenient transfer services. Second, optimal routes between stations were generated using network analysis and route optimization algorithms to improve the service coverage and operational efficiency of the airport shuttle. Finally, recommended routes were refined through manual adjustments of the optimal routes. A comparative analysis of route evaluation results revealed that the optimal airport shuttle routes significantly reduced the total walking distance of passengers. This study optimized airport bus station layout and route planning based on actual travel demand, providing scientific support for improving airport transfer services.

Key words: airport travel demand, demand center identification , airport shuttle bus, station selection, route optimization

CLC Number:

U491

HE Jia, ZHAO Xiaoqi. Research on the layout and route optimization of airport shuttle bus stations based on passenger travel demand data [J].Shandong Science, 0, (): 1-.

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Research on the layout and route optimization of airport shuttle bus stations based on passenger travel demand data

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