Research on Influencing Factors of Urban Road Traffic Casualties through Support Vector Machine

Huacai Xian (), Yu Wang, Yujia Hou, Shunzhong Dong, Junying Kou and Huili Zeng
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Huacai Xian: Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China
Yu Wang: Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China
Yujia Hou: Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China
Shunzhong Dong: Traffic Administration of Shandong Public Security Department, Jinan 250031, China
Junying Kou: Traffic Administration of Shandong Public Security Department, Jinan 250031, China
Huili Zeng: Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China

Sustainability, 2022, vol. 14, issue 23, 1-15

Abstract: Urban road traffic safety has always been vital in transportation research. This paper analyzed the factors influencing the degree of traffic accident casualties on Jinan Jingshi Road and its branch roads, taking them as the study area for urban road traffic safety problems. Additionally, it used the application of Particle Swarm Optimization (PSO), a Support Vector Machine (SVM) model, and a recursive feature elimination (RFE) to rank the contribution degree of the influencing factors. The results showed that driving on rainy days has a high probability of casualties, while the type of collision was a minimum influence factor. Additionally, on rainy days, cars were accident-prone road vehicles, and 8:00–12:00 and 18:00–22:00 were accident-prone periods. Based on the results, preventive measures were further put forward regarding the driver, road drainage capacity, policy management, and autopilot technology. This study aimed to guide urban traffic safety planning and provide a basis for developing traffic safety measures.

Keywords: urban road; accident casualty degree; SVM; the particle swarm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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