Assessing the Impact of Urban Morphology on Metro-Bicycle Sharing Transfers Using Random Forest Classification

Authors

  • Lei Gao School of Traffic and Transportation, Xi'an Traffic Engineering Institute, Xi'an, China
  • Jie Fu School of Economic and Management, Lanzhou University of Technology, Lanzhou, China
  • Deyang Kong School of Traffic and Transportation, Xi'an Traffic Engineering Institute, Xi'an, China | Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • Nabila Bte Abdul Ghani Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • Zuhra Junaida Binti Ir Mohamad Husny Hamid Universiti Teknologi Malaysia, Johor Bahru, Malaysia

DOI:

https://doi.org/10.23055/ijietap.2024.31.6.10173

Keywords:

Urban Morphology, Metro-Bicycle Sharing System, Built Environment, Random Forest Model, Cycling Pattern

Abstract

The urban built environment shapes the city's morphology, which possesses the capacity to influence the use of bike-sharing systems. Bike-sharing offers a solution to the "first-last mile" problem associated with metro systems, providing flexible and cost-effective means to enhance transit accessibility and reduce travel expenses. This study employs a bike-sharing trajectory dataset to analyze usage patterns and integrates urban morphology—defined by land use, Points of Interest (POIs), and spatial clusters of transportation facilities—to determine if the urban form can affect cycling behavior. The findings reveal that, in addition to urban morphological factors, bike-sharing usage patterns exhibit strong classification performance. The misclassification rates were 0.3439 for departures and 0.2472 for arrivals. The difference in misclassification rates can be attributed to the diverse urban contexts surrounding metro stations. For instance, stations located in residential areas tend to have more predictable bike-sharing patterns, resulting in lower misclassification rates. In contrast, stations in commercial zones with higher land-use diversity and Points of Interest (POIs) exhibit more variability in cycling behavior, leading to higher error rates. The research demonstrates that the spatial characteristics of urban morphology—such as land-use diversity and clustering of POIs—play a pivotal role in influencing metro-bicycle sharing patterns. The model achieved an 83.5% accuracy rate in distinguishing between bike-sharing rides to or from metro stations. These findings underscore the integrated role of urban form in shaping travel behavior, especially regarding the synergy between metro systems and bicycle-sharing.

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Published

2024-12-16

How to Cite

Gao, L., Fu, J., Kong, D., Abdul Ghani, N. B., & Mohamad Husny Hamid, Z. J. B. I. (2024). Assessing the Impact of Urban Morphology on Metro-Bicycle Sharing Transfers Using Random Forest Classification. International Journal of Industrial Engineering: Theory, Applications and Practice, 31(6). https://doi.org/10.23055/ijietap.2024.31.6.10173

Issue

Vol. 31 No. 6 (2024)

Section

Data Sciences and Computational Intelligence

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