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Impact of weather conditions on middle school students' commute mode choices: Empirical findings from Beijing, China

机译:天气状况对中学生通勤方式选择的影响:来自中国北京的实证研究

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摘要

Weather conditions have been recognized as important factors affecting school commute mode choices. This paper aims to explore the modal shift of middle school commutes with respect to the variation in weather-related variables, with empirical emphases on the situation in Beijing, China. Data from the latest Beijing School Commute Survey (2014-2015) were adopted, and multinomial probit (MNP) and multinomial logit (MNL) models were developed. The modeling results are in favor of the MNP model because it has better statistical performance. Weather related variables, including sky condition, wind speed, highest temperature, humidity, air quality index (AQI), and some interaction terms, were found to have a significant impact on students' commute mode choices. Based on these models, an empirical sensitivity measure was defined as the expected percentage change in the probability of choosing each mode with respect to an order of magnitude change in the influential factors. Most of the results are in line with those of previous studies, and some unique results reflect features of Beijing. For example, on days with extremely poor air quality, students are more likely to turn to public transport rather than use a car from active transportation modes. This is probably due to the special urban traffic regulations that restrict household car ownership and car travel in Beijing. These findings could have implications for promoting active transportation for students and serve as references for policy makers and planners.
机译:天气条件已被认为是影响学校上下班方式选择的重要因素。本文旨在探讨与天气相关变量变化有关的中学通勤方式转变,并以经验重点强调中国北京的情况。采用了最新的北京学校通勤调查(2014-2015年)数据,并开发了多项式概率(MNP)和多项式logit(MNL)模型。建模结果有利于MNP模型,因为它具有更好的统计性能。与天气相关的变量,包括天空状况,风速,最高温度,湿度,空气质量指数(AQI),以及一些相互作用项,被发现对学生上下班方式的选择有重要影响。基于这些模型,将经验敏感性度量定义为相对于影响因素的数量级变化,选择每种模式的可能性的预期百分比变化。大多数结果与以前的研究结果一致,一些独特的结果反映了北京的特点。例如,在空气质量极差的日子里,学生更有可能转向公共交通工具,而不是从主动交通工具上开车。这可能是由于特殊的城市交通法规限制了北京的家用车拥有量和汽车出行量。这些发现可能对促进学生的积极交通有影响,并为政策制定者和计划者提供参考。

著录项

  • 来源
    《Transportation Research》 |2019年第3期|39-51|共13页
  • 作者单位

    Beijing Jiaotong Univ, Sch Traff & Transportat, MOE Key Lab Urban Transportat Complex Syst Theory, Beijing 100044, Peoples R China;

    Beijing Inst Technol, Sch Mech Engn, Lab Digital Mfg, Beijing 100081, Peoples R China;

    Dalian Univ Technol, Sch Transportat & Logist, Dalian 116024, Peoples R China;

    Beijing Inst Technol, Sch Mech Engn, Lab Digital Mfg, Beijing 100081, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Weather condition; School commute; Mode choice; Multinomial probit model; Empirical sensitivity;

    机译:天气条件;学校通勤;模式选择;多项式概率模型;经验敏感性;
  • 入库时间 2022-08-18 04:23:16

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