A Review of Road Traffic Accident Prediction Methods

Wang Shunshun; Yan Changshun; Shao Yong

doi:doi:10.11648/j.ajmse.20230803.12

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A Review of Road Traffic Accident Prediction Methods

Wang Shunshun, Yan Changshun, Shao Yong

Published in American Journal of Management Science and Engineering (Volume 8, Issue 3)

Received: 20 April 2023 Accepted: 23 May 2023 Published: 29 May 2023

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Abstract

With the continuous development of urban traffic and the acceleration of urbanization, traffic accidents have become an important issue for urban safety and social stability. In order to prevent and reduce the occurrence of traffic accidents, traffic accident prediction technology has gradually become a hot spot for research. This paper analyzes road traffic accident prediction techniques from articles included in relevant English journals and provides a detailed introduction to the road traffic accident prediction techniques that are already in existence. This paper introduces the current status of research on traffic accident prediction techniques, including traditional statistical analysis methods, machine learning methods, neural network methods, time series analysis methods and techniques based on spatio-temporal data mining, and analyses the advantages and disadvantages of each road traffic accident prediction method. These methods are able to analyse the influencing factors of traffic accidents, build prediction models, improve prediction accuracy and provide strong support for road traffic accident prevention effects for urban traffic safety. Finally, the main difficulties faced in road traffic accident prediction and the future development trend of road traffic accident prediction is discussed. The work done in this paper can provide necessary theoretical support for relevant researchers and save the time needed for literature review.

Published in	American Journal of Management Science and Engineering (Volume 8, Issue 3)
DOI	10.11648/j.ajmse.20230803.12
Page(s)	73-77
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Road Traffic Accidents, Prediction Models, Time Series Analysis

References

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[10]	Wenqi, L., L. Dongyu and Y. Menghua, A model of traffic accident prediction based on convolutional neural network. 2017, IEEE. p. 198--202.
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APA Style

Wang Shunshun, Yan Changshun, Shao Yong. (2023). A Review of Road Traffic Accident Prediction Methods. American Journal of Management Science and Engineering, 8(3), 73-77. https://doi.org/10.11648/j.ajmse.20230803.12

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ACS Style

Wang Shunshun; Yan Changshun; Shao Yong. A Review of Road Traffic Accident Prediction Methods. Am. J. Manag. Sci. Eng. 2023, 8(3), 73-77. doi: 10.11648/j.ajmse.20230803.12

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AMA Style

Wang Shunshun, Yan Changshun, Shao Yong. A Review of Road Traffic Accident Prediction Methods. Am J Manag Sci Eng. 2023;8(3):73-77. doi: 10.11648/j.ajmse.20230803.12

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@article{10.11648/j.ajmse.20230803.12,
  author = {Wang Shunshun and Yan Changshun and Shao Yong},
  title = {A Review of Road Traffic Accident Prediction Methods},
  journal = {American Journal of Management Science and Engineering},
  volume = {8},
  number = {3},
  pages = {73-77},
  doi = {10.11648/j.ajmse.20230803.12},
  url = {https://doi.org/10.11648/j.ajmse.20230803.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20230803.12},
  abstract = {With the continuous development of urban traffic and the acceleration of urbanization, traffic accidents have become an important issue for urban safety and social stability. In order to prevent and reduce the occurrence of traffic accidents, traffic accident prediction technology has gradually become a hot spot for research. This paper analyzes road traffic accident prediction techniques from articles included in relevant English journals and provides a detailed introduction to the road traffic accident prediction techniques that are already in existence. This paper introduces the current status of research on traffic accident prediction techniques, including traditional statistical analysis methods, machine learning methods, neural network methods, time series analysis methods and techniques based on spatio-temporal data mining, and analyses the advantages and disadvantages of each road traffic accident prediction method. These methods are able to analyse the influencing factors of traffic accidents, build prediction models, improve prediction accuracy and provide strong support for road traffic accident prevention effects for urban traffic safety. Finally, the main difficulties faced in road traffic accident prediction and the future development trend of road traffic accident prediction is discussed. The work done in this paper can provide necessary theoretical support for relevant researchers and save the time needed for literature review.},
 year = {2023}
}

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TY  - JOUR
T1  - A Review of Road Traffic Accident Prediction Methods
AU  - Wang Shunshun
AU  - Yan Changshun
AU  - Shao Yong
Y1  - 2023/05/29
PY  - 2023
N1  - https://doi.org/10.11648/j.ajmse.20230803.12
DO  - 10.11648/j.ajmse.20230803.12
T2  - American Journal of Management Science and Engineering
JF  - American Journal of Management Science and Engineering
JO  - American Journal of Management Science and Engineering
SP  - 73
EP  - 77
PB  - Science Publishing Group
SN  - 2575-1379
UR  - https://doi.org/10.11648/j.ajmse.20230803.12
AB  - With the continuous development of urban traffic and the acceleration of urbanization, traffic accidents have become an important issue for urban safety and social stability. In order to prevent and reduce the occurrence of traffic accidents, traffic accident prediction technology has gradually become a hot spot for research. This paper analyzes road traffic accident prediction techniques from articles included in relevant English journals and provides a detailed introduction to the road traffic accident prediction techniques that are already in existence. This paper introduces the current status of research on traffic accident prediction techniques, including traditional statistical analysis methods, machine learning methods, neural network methods, time series analysis methods and techniques based on spatio-temporal data mining, and analyses the advantages and disadvantages of each road traffic accident prediction method. These methods are able to analyse the influencing factors of traffic accidents, build prediction models, improve prediction accuracy and provide strong support for road traffic accident prevention effects for urban traffic safety. Finally, the main difficulties faced in road traffic accident prediction and the future development trend of road traffic accident prediction is discussed. The work done in this paper can provide necessary theoretical support for relevant researchers and save the time needed for literature review.
VL  - 8
IS  - 3
ER  -

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Author Information

Wang Shunshun

Faculty of information Technology, Beijing University of Technology, Beijing, China
Yan Changshun

Faculty of information Technology, Beijing University of Technology, Beijing, China
Shao Yong

Faculty of information Technology, Beijing University of Technology, Beijing, China

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Plain Text BibTeX RIS

APA Style

Wang Shunshun, Yan Changshun, Shao Yong. (2023). A Review of Road Traffic Accident Prediction Methods. American Journal of Management Science and Engineering, 8(3), 73-77. https://doi.org/10.11648/j.ajmse.20230803.12

Copy | Download

ACS Style

Wang Shunshun; Yan Changshun; Shao Yong. A Review of Road Traffic Accident Prediction Methods. Am. J. Manag. Sci. Eng. 2023, 8(3), 73-77. doi: 10.11648/j.ajmse.20230803.12

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AMA Style

Wang Shunshun, Yan Changshun, Shao Yong. A Review of Road Traffic Accident Prediction Methods. Am J Manag Sci Eng. 2023;8(3):73-77. doi: 10.11648/j.ajmse.20230803.12

Copy | Download

@article{10.11648/j.ajmse.20230803.12,
  author = {Wang Shunshun and Yan Changshun and Shao Yong},
  title = {A Review of Road Traffic Accident Prediction Methods},
  journal = {American Journal of Management Science and Engineering},
  volume = {8},
  number = {3},
  pages = {73-77},
  doi = {10.11648/j.ajmse.20230803.12},
  url = {https://doi.org/10.11648/j.ajmse.20230803.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20230803.12},
  abstract = {With the continuous development of urban traffic and the acceleration of urbanization, traffic accidents have become an important issue for urban safety and social stability. In order to prevent and reduce the occurrence of traffic accidents, traffic accident prediction technology has gradually become a hot spot for research. This paper analyzes road traffic accident prediction techniques from articles included in relevant English journals and provides a detailed introduction to the road traffic accident prediction techniques that are already in existence. This paper introduces the current status of research on traffic accident prediction techniques, including traditional statistical analysis methods, machine learning methods, neural network methods, time series analysis methods and techniques based on spatio-temporal data mining, and analyses the advantages and disadvantages of each road traffic accident prediction method. These methods are able to analyse the influencing factors of traffic accidents, build prediction models, improve prediction accuracy and provide strong support for road traffic accident prevention effects for urban traffic safety. Finally, the main difficulties faced in road traffic accident prediction and the future development trend of road traffic accident prediction is discussed. The work done in this paper can provide necessary theoretical support for relevant researchers and save the time needed for literature review.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - A Review of Road Traffic Accident Prediction Methods
AU  - Wang Shunshun
AU  - Yan Changshun
AU  - Shao Yong
Y1  - 2023/05/29
PY  - 2023
N1  - https://doi.org/10.11648/j.ajmse.20230803.12
DO  - 10.11648/j.ajmse.20230803.12
T2  - American Journal of Management Science and Engineering
JF  - American Journal of Management Science and Engineering
JO  - American Journal of Management Science and Engineering
SP  - 73
EP  - 77
PB  - Science Publishing Group
SN  - 2575-1379
UR  - https://doi.org/10.11648/j.ajmse.20230803.12
AB  - With the continuous development of urban traffic and the acceleration of urbanization, traffic accidents have become an important issue for urban safety and social stability. In order to prevent and reduce the occurrence of traffic accidents, traffic accident prediction technology has gradually become a hot spot for research. This paper analyzes road traffic accident prediction techniques from articles included in relevant English journals and provides a detailed introduction to the road traffic accident prediction techniques that are already in existence. This paper introduces the current status of research on traffic accident prediction techniques, including traditional statistical analysis methods, machine learning methods, neural network methods, time series analysis methods and techniques based on spatio-temporal data mining, and analyses the advantages and disadvantages of each road traffic accident prediction method. These methods are able to analyse the influencing factors of traffic accidents, build prediction models, improve prediction accuracy and provide strong support for road traffic accident prevention effects for urban traffic safety. Finally, the main difficulties faced in road traffic accident prediction and the future development trend of road traffic accident prediction is discussed. The work done in this paper can provide necessary theoretical support for relevant researchers and save the time needed for literature review.
VL  - 8
IS  - 3
ER  -

Copy | Download