建筑环境对中国公交导向型中等城市出行距离的影响

IF 1.6 4区 工程技术 Q4 TRANSPORTATION
Xiaowei Li, Lanxin Shi, Ju Tang, Jiaying Li, Pengjun Zhao, Qian Liu, Jun Chen, Changxi Ma
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引用次数: 0

摘要

建筑环境和天气条件对旅行行为的影响已被广泛研究。然而,对于如何更好地理解公交导向型中等城市的这种影响,特别是从旅客出发地和目的地的不同角度进行的研究还很有限。我们以中国渭南为代表,研究了发展中国家集中采用公交导向发展战略的二线城市。通过将 XGBoost 和 Shapley Additive Explanation(SHAP)与多源数据相结合的可解释机器学习方法,我们发现了特征重要性和关键因素非线性效应的新证据。大多数关键因素在出发地和目的地都至关重要,例如住宅和商业设施的密度。然而,道路密度和登机时间等几个重要因素对旅行行为的影响却极不平衡。这些发现为中等城市的城市规划策略提供了新颖的见解和经验启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of the built environment on travel distance in bus-oriented, medium-sized cities in China
The impact of the built environment and weather conditions on travel behavior has been widely studied. However, limited studies have focused on better understanding such effects in medium-sized cities with bus-oriented transit systems, particularly from a separate perspective of travelers’ origins and destinations. We took Weinan, China, as a representative of second-tier cities in developing countries that concentrate on bus-oriented development strategies. New evidence of feature importance and nonlinear effects of crucial factors were revealed by an interpretable machine learning-based approach combining XGBoost and Shapley Additive Explanation (SHAP) with multi-source data. Most key factors were critical at both origins and destinations, such as the density of residential and commercial facilities. However, several important factors, such as road density and boarding time, had strong imbalanced effects on travel behavior. These findings provide novel insights and empirical implications to support urban planning strategies in medium-sized cities.
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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