新冠疫情对城市核心区交通安全的干预效应分析

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (6): 84-90.

新冠疫情对城市核心区交通安全的干预效应分析

赵丹¹，王景升^*1，周妍²，刘东¹，邢立利³

1. 中国人民公安大学治安与交通管理学院，北京 102163；2. 浙江警察学院交通管理系，杭州 310053； 3. 浙江省宁波市交通警察局，浙江宁波 315100

收稿日期:2020-07-04 修回日期:2020-08-30 出版日期:2020-12-25 发布日期:2020-12-25
作者简介:赵丹(1983-)，女，吉林四平人，讲师.
基金资助:
中央高校基本科研业务费专项基金/ Fundamental Research Funds for the Central Universities of Ministry of Education of China(2020JWCX13, 2020JKF202)；中国人民公安大学“新冠肺炎疫情防控背景下的警务创新”专项项目/The People's Public Security University of China "Police Innovation in the Context of COVID-19 Epidemic Prevention and Control" Special Project(2020JWCX13).

Intervention Effect Analysis on Traffic Safety in Urban Core Areas under Influence of COVID-19

ZHAO Dan¹, WANG Jing-sheng¹, ZHOU Yan², LIU Dong¹, XING Li-li³

1. School of Public Order and Traffic Management, People's Public Security University of China, Beijing 102163, China; 2. Department of Traffic Management Engineering, Zhejiang Police College, Hangzhou 310053, China; 3. Traffic Police Station of Ningbo City, Ningbo 315100, Zhejiang, China

Received:2020-07-04 Revised:2020-08-30 Online:2020-12-25 Published:2020-12-25

摘要/Abstract

摘要：

新冠疫情政策使城市核心区交通安全特征发生变化.本文利用交通事故接处警数据构建一维时间序列，分析疫情下交通事故的时间分布特征；针对交通事故量序列的非平稳特征，运用小波分解技术提取疫情防控政策干预下的序列结构突变点，该突变点排除春节假日因素的影响；结合支持向量机方法构建疫情防控政策对交通事故量影响的干预模型，评估疫情对交通事故量的影响程度.研究结果表明：疫情初期的管控政策使交通事故量平均每日下降12.23起，先以68.7%的速度衰减，又以30.9%的速度回升，该趋势一直持续到复工复产政策实施，相对宽松的交通管控政策使平均每日事故量下降值稳定在11.71起.

关键词: 城市交通, 干预分析, 小波分析, 交通安全, 支持向量机, 新冠疫情

Abstract:

The traffic safety characteristics were changed in urban core areas under the influence of COVID-19. In this paper, a one- dimensional time series was constructed based on the data of traffic accident reception and handling. Through the descriptive analysis, the time distribution characteristics of traffic accident under COVID-19 epidemic was studied. In view of the non- stationary characteristics of traffic accident sequence, wavelet decomposition technology was used to extract the structural mutation point of the sequence under the COVID-19 controlling policies, which excluded the influence of the Spring Festival holiday. With the supported vector machine(SVM) method, an intervention model was established to evaluate the impact of COVID-19 epidemic prevention policies on traffic accidents. The research results show that the rigor traffic prevention policies have reduced the daily traffic accident rate by 12.23 on average, and then it attenuates at a rate of 68.7%, and then to recover at a rate of 30.9%, which lasts until the implementation of the policy of resuming work and production; and the relatively lenient traffic control policies stabilizes the reduction of daily accident rate at 11.707 on average.

Key words: urban traffic, intervention analysis, wavelet analysis, traffic safety, supported vector machine, COVID-19

中图分类号:

U491.3

赵丹，王景升，周妍，刘东，邢立利. 新冠疫情对城市核心区交通安全的干预效应分析[J]. 交通运输系统工程与信息, 2020, 20(6): 84-90.

ZHAO Dan, WANG Jing-sheng, ZHOU Yan, LIU Dong, XING Li-li. Intervention Effect Analysis on Traffic Safety in Urban Core Areas under Influence of COVID-19[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(6): 84-90.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract20152.shtml

http://www.tseit.org.cn/CN/Y2020/V20/I6/84

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