Parking choice behavior analysis of rural residents based on latent variable random forest model

IF 2.7 4区 工程技术 Q2 TRANSPORTATION SCIENCE & TECHNOLOGY Transportation Safety and Environment Pub Date : 2023-12-23 DOI:10.1093/tse/tdad045
Minqing Zhu, Bo Zhao, Hongjun Cui, Sheng Yao, Feng Xu
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Abstract

The imbalance of rural parking supply and demand has a great impact on traffic congestion and environmental pollution, which has attracted the attention of many scholars as well as policymakers. However, most of the current research on parking choice mainly focuses on urban business and residential areas, lacks research on rural parking choice behavior, and focuses on the analysis of observable factors, ignoring the internal relationship with potential variables. Based on this, this study considers the heterogeneity of individuals and uses the random forest algorithm to construct a model of rural residents’ willingness to choose parking with both latent and explicit variables, to explore how much and in what ways individual characteristics and parking characteristics affect rural residents’ parking choices, and to explore parking planning programs and strategies that are truly applicable to rural areas. The results of the study suggest that safety and convenience of the parking environment are key factors influencing the parking choice behavior of rural residents, and can greatly improve the predictive accuracy of the parking willingness model. Upon comparison, it is found that the application of the random forest algorithm is also significantly better than the logit model in terms of prediction effect, indicating that there is a nonlinear effect among the factors influencing the parking choice behavior of rural residents and that the random forest model with the addition of latent variables provides a better explanatory ability for the study of the parking choice behavior of rural residents.
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基于潜变量随机森林模型的农村居民停车选择行为分析
农村停车供需失衡对交通拥堵和环境污染影响巨大,已引起众多学者和政策制定者的关注。然而,目前大多数关于停车选择的研究主要集中在城市商业区和居住区,缺乏对农村停车选择行为的研究,且侧重于对可观测因素的分析,忽视了与潜在变量的内在关系。基于此,本研究考虑了个体的异质性,采用随机森林算法构建了包含潜变量和显变量的农村居民停车选择意愿模型,探讨个体特征和停车特征对农村居民停车选择的影响程度和影响方式,探索真正适用于农村地区的停车规划方案和策略。研究结果表明,停车环境的安全性和便利性是影响农村居民停车选择行为的关键因素,可以大大提高停车意愿模型的预测精度。通过比较发现,应用随机森林算法的预测效果也明显优于Logit模型,说明农村居民停车选择行为的影响因素之间存在非线性效应,加入潜变量的随机森林模型为农村居民停车选择行为的研究提供了更好的解释能力。
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来源期刊
Transportation Safety and Environment
Transportation Safety and Environment TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
3.90
自引率
13.60%
发文量
32
审稿时长
10 weeks
期刊最新文献
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