Influences of built environment on intercity travel demand of urban agglomerations: The discrepancies across inferred trip purposes

IF 6.6 1区经济学 Q1 URBAN STUDIES

Cities Pub Date : 2025-09-02 DOI:10.1016/j.cities.2025.106404

Zile Liu , Xiaobing Liu , Xuedong Yan , Fengxiao Li , Hua Zhong , Yun Wang

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引用次数: 0

Abstract

With the expansion of urbanization, numerous urban agglomerations have emerged, significantly intensifying intercity interactions with diverse purposes. While previous studies have highlighted the significant role of the built environment in shaping travel demand, research on its influences on intercity travel within urban agglomerations, particularly across different trip purposes, remains insufficient. To address this gap, this study proposes a data-driven methodology that includes trip purpose inference algorithm and explainable spatial deep learning model. Specifically, using mobile phone signaling data of the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA) in China, we develop a rule-based algorithm involving travel patterns to infer intercity trip purpose, the thresholds of which are determined through a traveler-based sampling validation method. Subsequently, the geographically weighted neural network (GWNN) method, which effectively captures spatial heterogeneity and nonlinear relationships, is employed to investigate the influences of the built environment on different types of intercity travel. The results indicate that the proposed quantifying model outperforms benchmark models. The average contribution of distance, transportation, and socioeconomic variables have a greater influence than land-use variables, and the nonlinear effects of these variables show significant differences across various trip purposes. Notably, the factor of distance to Beijing influencing travel varies by purpose: commuting travel exerts a positive influence up to 120 km, leisure travel up to 160 km, and business travel up to 175 km. These findings underscore the critical importance of spatial governance in urban agglomerations, offering practical insights for planners to better align land use strategies with differentiated intercity travel demands, thereby facilitating coordinated regional development and efficient resource allocation.

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建成环境对城市群城际出行需求的影响：推断出行目的的差异

随着城市化的扩大，出现了大量的城市群，城市间的相互作用显著加强，目的多样。虽然以前的研究强调了建筑环境在形成旅行需求方面的重要作用，但对其对城市群内城际旅行的影响，特别是不同旅行目的之间的影响的研究仍然不足。为了解决这一差距，本研究提出了一种数据驱动的方法，包括旅行目的推理算法和可解释的空间深度学习模型。具体而言，利用京津冀城市群（BTHUA）的手机信令数据，我们开发了一种基于规则的基于出行模式的算法来推断城际出行目的，并通过基于旅行者的抽样验证方法确定了阈值。在此基础上，利用地理加权神经网络（GWNN）方法分析了不同类型城际交通对建成环境的影响，该方法能够有效地捕捉空间异质性和非线性关系。结果表明，所提出的量化模型优于基准模型。距离、交通和社会经济变量的平均贡献比土地利用变量的影响更大，这些变量的非线性效应在不同旅行目的之间表现出显著差异。值得注意的是，到北京的距离影响出行的因素因目的而异：通勤出行对120公里以内的人有正向影响，休闲出行对160公里以内的人有正向影响，商务出行对175公里以内的人有正向影响。这些研究结果强调了城市群空间治理的重要性，为规划人员更好地将土地利用策略与不同的城际旅行需求结合起来提供了实践见解，从而促进区域协调发展和有效的资源配置。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cities URBAN STUDIES-

CiteScore

11.20

自引率

9.00%

发文量

517

期刊介绍： Cities offers a comprehensive range of articles on all aspects of urban policy. It provides an international and interdisciplinary platform for the exchange of ideas and information between urban planners and policy makers from national and local government, non-government organizations, academia and consultancy. The primary aims of the journal are to analyse and assess past and present urban development and management as a reflection of effective, ineffective and non-existent planning policies; and the promotion of the implementation of appropriate urban policies in both the developed and the developing world.