Technical Papers
Sep 28, 2023

Efficiency Assessment of Transit-Oriented Development Focusing on the 500-m Core Catchment of Metro Stations Based on the Concept of a Metro Microcenter in Beijing

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 12

Abstract

Faced with the urban sprawl and the increasingly serious urban traffic problems caused by the sustained and rapid economic growth and fast development of urbanization, advocating the development of metro-led cities and intensive and compact development to form a green, transportation-oriented built environment has become a national strategic need. In order to promote the integrated development of stations and the city, and further enhance the vitality of the city, the concept of metro microcenter transportation was brought up in Beijing. A metro microcenter is a geographical space with full integration and interaction with metro stations, high accessibility, high degree of intensive land use, and multiple urban functions. Considering the characteristics of metro microcenters, the mechanism between passenger flow and the built environment in the general control and management area of a metro microcenter is worth studying. However, few previous studies have systematically and comprehensively carried out theoretical and empirical research on the relationship between the built environment and multimodal public transport passenger flow characteristics around metro station catchments. Based on the 500-m metro core station catchment, this study introduced the data envelopment analysis (DEA) method, and a highly efficient and refined public travel efficiency assessment model (Bootstrap-Super-DEA) was proposed to evaluate the transit-oriented development (TOD) level of the existing metro core station catchment. Metro station passenger flow, bus station passenger flow, and shared-bicycle passenger flow were selected as output variables of this model. Network centrality, functional mix, and other building environment indicators were selected as input variables of this model. In addition, the derived indicators of passenger flow were extracted to reveal the relationship with efficiency from the spatiotemporal distribution characteristics. The model effectively distinguishes the distribution of metro core station catchments with efficient TOD. The study results can provide a reference for metro microcenter planning managers to grasp the core station catchment’s development tone accurately.

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Data Availability Statement

Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions:
1.
AFC data, bus data, and shared-bicycle data: These data cooperate with the Beijing transportation system, and our permission is only allowed to deploy the algorithm on their data platform and calculate the results. Meanwhile, the data cannot be taken out. Therefore, these data are provided with restrictions.
2.
Indicators extraction algorithm: the corresponding author’s related codes are available if requested.
3.
Efficiency evaluation method: this code is also available from the corresponding author if requested.

Acknowledgments

We gratefully acknowledge the research funding support for this project provided through the Zhejiang University Integrated Transportation and Intelligent Transportation (Project No. 2018YFB1600904). Thanks also for the contribution to the paper.
Author contributions: Tingzhao Chen, Yanyan Chen, Yuyang Zhou, and Jifu Guo contributed to the study conception and design. Tingzhao Chen, Yanyan Chen, and Yuyang Zhou contributed to the data collection. Tingzhao Chen, Yanyan Chen, and Jifu Gu contributed to the analysis and interpretation of results. Tingzhao Chen and Yuyang Zhou contributed to the draft manuscript preparation.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 149Issue 12December 2023

History

Received: Feb 15, 2022
Accepted: Jan 23, 2023
Published online: Sep 28, 2023
Published in print: Dec 1, 2023
Discussion open until: Feb 28, 2024

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Tingzhao Chen, Ph.D. [email protected]
Lecturer, School of Transportation, Shandong Jianzhu Univ., Jinan 250101, China. Email: [email protected]
Yanyan Chen, Ph.D. [email protected]
Professor, Beijing Key Laboratory of Traffic Engineering, Beijing Univ. of Technology, Beijing 100124, China (corresponding author). Email: [email protected]
Yuyang Zhou, Ph.D. [email protected]
Associate Professor, Beijing Key Laboratory of Traffic Engineering, Beijing Univ. of Technology, Beijing 100124, China. Email: [email protected]
Jifu Guo, Ph.D. [email protected]
Professor, Beijing Transportation Institute, Beijing 100161, China. Email: [email protected]

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