Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China

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...

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Autores principales:	Hongjun Xiong, Yi Shen*, Liyou Fu
Formato:	article
Lenguaje:	EN
Publicado:	Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2021
Materias:	accident prediction ARIMA model freeway influence factors safety evaluation Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/bce878672ced474f869f2d1f8ff22351
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id	oai:doaj.org-article:bce878672ced474f869f2d1f8ff22351
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spelling	oai:doaj.org-article:bce878672ced474f869f2d1f8ff223512021-11-07T00:34:42ZTraffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China1330-36511848-6339https://doaj.org/article/bce878672ced474f869f2d1f8ff223512021-01-01T00:00:00Zhttps://hrcak.srce.hr/file/383554https://doaj.org/toc/1330-3651https://doaj.org/toc/1848-6339In 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.Hongjun XiongYi Shen*Liyou FuFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek articleaccident predictionARIMA modelfreewayinfluence factorssafety evaluationEngineering (General). Civil engineering (General)TA1-2040ENTehnički Vjesnik, Vol 28, Iss 6, Pp 1904-1911 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	accident prediction ARIMA model freeway influence factors safety evaluation Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	accident prediction ARIMA model freeway influence factors safety evaluation Engineering (General). Civil engineering (General) TA1-2040 Hongjun Xiong Yi Shen* Liyou Fu Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
description	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.
format	article
author	Hongjun Xiong Yi Shen* Liyou Fu
author_facet	Hongjun Xiong Yi Shen* Liyou Fu
author_sort	Hongjun Xiong
title	Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
title_short	Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
title_full	Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
title_fullStr	Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
title_full_unstemmed	Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China
title_sort	traffic safety evaluation and accident prediction of freeway: evidence from china
publisher	Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
publishDate	2021
url	https://doaj.org/article/bce878672ced474f869f2d1f8ff22351
work_keys_str_mv	AT hongjunxiong trafficsafetyevaluationandaccidentpredictionoffreewayevidencefromchina AT yishen trafficsafetyevaluationandaccidentpredictionoffreewayevidencefromchina AT liyoufu trafficsafetyevaluationandaccidentpredictionoffreewayevidencefromchina
_version_	1718443635442188288

Traffic Safety Evaluation and Accident Prediction of Freeway: Evidence from China

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