新冠肺炎防护措施对学生市内出行习惯的影响——以巴尔干地区中型大学城为例

N. Jurišević, Miroslav Stojadinović, D. Končalović, Nikola Rakić, R. Kowalik, D. Gordić
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引用次数: 0

摘要

在建立社区旅行模式之前,实施保护公众健康和预防COVID-19疾病不受控制的传播的措施。科学界因此想知道的一个问题是,所发生的情况是否有可能给社区旅行行为带来永久性的改变。在这方面,本研究考察了巴尔干半岛一个中型大学城学生旅行习惯的变化。这项研究基于486名学生在COVID-19大流行之前和期间通过b谷歌问卷收集的回答。本研究包括数据解释和数据分析。在引入的六个分类模型中,随机森林被证明是最适合准确拟合学生的人口统计细节和学生对未来旅行习惯的态度(改变或不改变)。并对模型进行了优化,进一步分析了变量影响和变量偏相关。数据解释表明,对私家车依赖程度的提高是拥有两辆私家车的家庭增加15%的原因。因此,在疫情期间步行上学的学生比例下降了约20%,而使用公共交通工具的学生比例保持相对不变(下降了约3%)。另一方面,使用六种分类模型中的最佳模型来确定导致学生对市中心交通态度永久变化的因素。衍生的分类模型推断出旅行模式的潜在永久变化——距离大学2至4公里之间的距离,以及其中的学生——那些访问讲座的次数比其他人少的学生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Changes in students’ inner-city traveling habits caused by protective measures against COVID-19 disease – example of the medium-sized university city in the Balkans
Imposed measures for the protection of public health and prevention of the uncontrolled spread of COVID-19 disease affected before established community traveling patterns. One of the questions scientific community consequently wonders consider the potentials of the occurred circumstances to leave permanent change to community traveling behavior. With that regard, this study examines changes in students’ traveling habits in a medium-sized university city in the Balkans. The research was based on 486 students’ responses amassed by Google questionnaires, before and during the COVID-19 pandemic. The study includes data interpretation and data analysis. Among six introduced classification models, random forest proved as the most suitable to accurately fit the students’ demographic details to students’ attitude towards future traveling habits (as changed or not changed permanently). Additionally, the model was optimized and further analyzed on variable influence and variable partial dependence. Data interpretation indicates higher reliance on personal automobiles as a cause for a 15% increase of the families owning two of the vehicles. Because of that, the share of the students who walked to the University during the pandemic declined by approximately 20%, while those using public transportation stayed relatively unchanged (decrease by around 3%). On the other side, the best of six classification models was used to determine the factors causing a permanent change in students’ attitudes towards inner-city transportation. Derived classification models deduce where to expect potentially permanent changes in traveling patterns – distances between 2 and 4 km from the University, and among which students – those who are visiting lectures less frequently than others.
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