影响因子：1.6

所属单位：西安建筑科技大学

发表刊物：Journal of Transport and Land Use

关键字：Travel distance; Bus transit systems; Built environment; Medium-sized cities; Machine learning; Big data

摘要：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.

合写作者：石兰馨,汤俊卿,赵鹏军,李嘉颖,刘倩,陈君,马昌喜

第一作者：李晓伟

论文类型：期刊论文

学科门类：工学

一级学科：交通运输工程

文献类型：J

是否译文：否

发表时间：2024-01-01

收录刊物：SSCI