A classification and recognition model for the severity of road traffic accident

A classification and recognition method for the severity of road traffic accident based on rough set theory and support vector machine was proposed in this article. Rough set theory was used to calculate the importance of attributes in human, vehicle, road, environment, and accident. On the basis of importance ranking, the factors affecting the severity of accident were extracted. Then, with the general accident and major accident as two classification labels, the classification and recognition model of the severity of road traffic accident was established by using support vector machine. The results show that the model could improve the recognition accuracy and reduce the computational workload. Moreover, it has the good ability in classification and recognition as well as generalization compared with the model using support vector machine alone.

• Record URL:
  https://doi.org/10.1177/1687814019851893
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/16878132
• Supplemental Notes:
  • © The Author(s) 2019.
• Authors:
  • Jianfeng, Xi
  • 0000-0002-4488-0850
  • Hongyu, Guo
  • Jian, Tian
  • Liu, Lisa
  • Haizhu, Liu
• Publication Date: 2019-5

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Serial:
  • Advances in Mechanical Engineering
  • Volume: 11
  • Issue Number: 5
  • Publisher: Sage Publications, Incorporated
  • ISSN: 1687-8132
  • EISSN: 1687-8140
  • Serial URL: https://journals.sagepub.com/home/ade
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Algorithms; Classification; Crash severity; Machine learning; Traffic crashes
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01769630
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 19 2021 5:19PM