摘要
在城市大学生人数众多、学校周边生活设施不完善、出行方式日趋多样化的背景下,研究以济南市为例,将城市分为中心城区、新区和外围区进行样本数据调查,通过统计分析及构建多元有序Probit回归模型、多元线性回归模型探索了高校大学生出行特征和出行行为影响因素的空间分异。研究发现对于出行频率,中心城区最高,外围区次之,新区最低;区位、性别、年级通过了显著性检验;而且区位与之呈负相关,性别、年级与之成正相关;专业未通过显著性检验。对于出行距离,性别对总出行距离和购物出行距离影响显著,而年级和专业对其影响不显著;区位、出行目的与出行距离呈正相关,性别、出行方式与出行距离呈负相关;不同区位大学生出行距离具有显著差异,且距离比值近似为1:2:3。出行方式在各个区位的影响都十分显著。
Under the background of the large number of college students in the city,the imperfect living facilities around the school and the increasingly diversified travel modes,this paper takes Jinan City as an example,divides the city into central urban area,new area and peripheral area for sample data investigation.Through statistical analysis and construction of multiple ordered probit regression model and multiple linear regression model,this paper explores the spatial differentiation of College Students'travel characteristics and influencing factors of travel behavior.The study found that for the travel frequency,the central urban area is the highest,the peripheral area is the second,and the new area is the lowest;the location,gender and grade have passed the significance test;moreover,the location has a negative correlation with it,gender and grade have a positive correlation with it;the major has not passed the significance test.For the travel distance,gender has a significant impact on the total travel distance and shopping travel distance,while grade and major have no significant impact on it;location,travel purpose and travel distance are positively correlated,gender,travel mode and travel distance are negatively correlated;the travel distance of college students in different locations is significantly different,and the distance ratio is approximately 1:2:3.The impact of travel mode in each location is very significant.
作者
梁维维
LIANG Weiwei(School of Traffic Engineering,Shandong Jianzhu University,Jinan,Shandong,250101,China)
出处
《智能城市应用》
2020年第1期116-120,共5页
Smart City Application
关键词
区位
大学生
出行特征
空间分异
location
college students
travel characteristics
spatial differentiation