全国道路交通安全水平的时空布局演化研究*

doi:10.16265/j.cnki.issn1003-3033.2021.12.018

中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (12): 136-143.doi: 10.16265/j.cnki.issn1003-3033.2021.12.018

全国道路交通安全水平的时空布局演化研究^*

李杰¹ 副研究员, 曾叙砜², 孙领³, 刘伟³, 李平⁴

1 中国科学院文献情报中心, 北京 100190;
2 宁波舟山港股份有限公司, 浙江宁波 315000;
3 上海海事大学交通运输学院,上海 201306;
4 深圳市都市交通规划设计研究院有限公司,广东深圳 518058

收稿日期:2021-09-22 修回日期:2021-11-14 出版日期:2021-12-28 发布日期:2022-06-28
作者简介:李杰 (1987—),男,陕西宝鸡人,博士,副研究员,主要从事安全科学管理、学术传承与学术创新效应以及安全科学计量与知识图谱研究。E-mail: lijie_jerry@126.com。
基金资助:
国家自然科学基金资助(51904185)。

Research on temporal and spatial evolution of road safety in China

LI Jie¹, ZENG Xufeng², SUN Ling³, LIU Wei³, LI Ping⁴

1 National Science Library, Chinese Academy of Sciences, Beijing 100190, China;
2 Ningbo Zhoushan Port Company Limited, Ningbo Zhejiang 315000, China;
3 College of Transport & Communications,Shanghai Maritime University ,Shanghai 201306,China;
4 Shenzhen Urban Transport Planning & Design Institute, Shenzhen Guangdong 518058, China

Received:2021-09-22 Revised:2021-11-14 Online:2021-12-28 Published:2022-06-28

摘要/Abstract

摘要： 为了解全国道路交通安全水平的时空布局演化特征,为区域交通规划提供依据,基于2001—2018年31个省市自治区面板数据,运用主成分分析法分析各地区的道路交通安全水平;并用ArcGIS软件对其可视化;最后用探索性空间数据分析法(ESDA)对整体及局部地区分别进行空间相关性分析。研究结果表明:2001—2018年全国道路交通事故发生起数整体呈下降趋势,全国道路交通安全水平的全局集聚性从2005年的显著集聚向2018年的随机性转化。2005年,吉林、四川为显著的高高类型地区,西藏为显著的低高类型区域,浙江、广东为显著的低低类型区域,山西为显著的低高类型区域。2010年,山东、河南为显著的高高类型区域,山西为显著的低高类型区域,广东为显著的低低类型区域。2015年,四川、山西、辽宁为显著的高高类型区域,广东为显著的低低类型区域。2018年,江苏为显著的高高类型区域,广东、湖南为显著的高低类型区域。

关键词: 道路交通安全水平, 时空布局, 主成分分析, 面板数据, 探索性空间数据分析(ESDA)

Abstract: In order to study temporal and spatial evolution characteristics of China's road safety level and provide a basis for regional transportation planning, based on panel data of 31 provinces and autonomous regions in China from 2001 to 2018, principal component analysis method was used to calculate road safety level of each region, which was then visualized by employing ArcGIS software. Then, spatial correlation analysis was conducted on the whole and local regions by ESDA. The results show that the total number of traffic accidents in China has declined in 2001-2018, and the global agglomeration of national road traffic safety level has transformed from significant agglomeration in 2005 to the randomness in 2018. In 2005, Jilin and Sichuan were significant high-high areas, while Tibet was a significant low-high area, and Zhejiang and Guangdong were significant low-low areas. In 2010, Shandong and Henan became significant areas of high-high types, Shanxi was that of low-high types, and Guangdong became low-low area. In 2015, Sichuan, Shanxi, and Liaoning were marked areas of high-high types, but Guangdong were marked areas of low-low types. In 2018, Jiangsu was a significant high-high area, and Guangdong and Hunan were significant high-low ones.

Key words: road traffic safety level, spatial distribution, principal component analysis, panel data, exploratory spatial data analysis (ESDA)

中图分类号:

X951

李杰, 曾叙砜, 孙领, 刘伟, 李平. 全国道路交通安全水平的时空布局演化研究^*[J]. 中国安全科学学报, 2021, 31(12): 136-143.

LI Jie, ZENG Xufeng, SUN Ling, LIU Wei, LI Ping. Research on temporal and spatial evolution of road safety in China[J]. China Safety Science Journal, 2021, 31(12): 136-143.

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全国道路交通安全水平的时空布局演化研究^*

Research on temporal and spatial evolution of road safety in China

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