Technical gazette, Vol. 28 No. 6, 2021.
Original scientific paper
https://doi.org/10.17559/TV-20210504115608
Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
Hongjun Xiong
; School of Business, Shanghai Dianji University, 300 Shuihua Road, Pudong New Area District, Shanghai, 201306, China
Yi Shen*
; Higher Education Research Institute, Shanghai University of Engineering Science, 333 Longteng Road, Songjiang District, Shanghai, 201620, China
Liyou Fu
; School of Business, Shanghai Dianji University, 300 Shuihua Road, Pudong New Area District, Shanghai, 201306, China
Abstract
In recent years, freeway safety accidents occurred frequently, causing serious harm to people's lives and property safety. Therefore, how to evaluate freeway traffic safety and predict the number of accidents scientifically is a practical problem to be solved. The influencing factors of freeway traffic safety could be summarized as human behaviour characteristics, vehicle factors, road factors, environmental factors and traffic safety factors after a systematic analysis. To evaluate traffic safety and predicate freeway accident, using the data of Zhejiang province, China from 2015 to 2019, a freeway safety evaluation system was constructed. The freeway safety level was measured by using hierarchical entropy method, and the future traffic accidents in the sample area were predicted by using the Autoregressive Integrated Moving Average (ARIMA) model. Results show that the traffic safety level of freeway in the sample areas presents a fluctuating upward trend, and has a relatively safe state with a safety level 2. The average error rate is only 0.47% in the predication of freeway accident, showing a high degree of fitting and accuracy. Based on the above conclusions, this study puts forward the corresponding improvement strategies to provide a scientific basis for the decision-making of the government and transportation departments.
Keywords
accident prediction; ARIMA model; freeway; influence factors; safety evaluation
Hrčak ID:
264048
URI
Publication date:
7.11.2021.
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