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Efficient road traffic anti-collision warning system based on fuzzy nonlinear programming

Author

Listed:
  • Fei Peng

    (Anhui Sanlian University)

  • Yanmei Wang

    (Anhui Sanlian University)

  • Haiyang Xuan

    (Anhui Hongtai Traffic Engineering Design and Research Institute Co, Ltd)

  • Tien V. T. Nguyen

    (Industrial University of Ho Chi Minh City)

Abstract

To improve the anti-collision warning system of road traffic, a research based on fuzzy nonlinear programming is proposed. People hope to know the accident in advance, and then take the corresponding protective measures to avoid accidents, to achieve the purpose of reducing the number of accidents. The specific content of this method is to establish a safety distance model to prevent rear-end collision. The following process can be divided into three situations: the leading vehicle is stationary, the leading vehicle is at uniform speed or accelerating speed, and the leading vehicle is decelerating. The mathematical model of the safe distance of overtaking are established respectively. The fuzzy mathematical theory is used to consider the influence of external environmental factors such as weather conditions, road condition, and vehicle speed. Determine the parameters involved in the model and the fuzzy relationship between some parameters and each influencing factor. The simulation model of vehicle anti-collision warning system is established by using fuzzy inference rules of some parameters, respectively, and the simulation test is conducted. The test results verify the rationality of the safety distance model and parameter setting. It can effectively reduce false alarm and improve the road traffic collision warning system.

Suggested Citation

  • Fei Peng & Yanmei Wang & Haiyang Xuan & Tien V. T. Nguyen, 2022. "Efficient road traffic anti-collision warning system based on fuzzy nonlinear programming," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 456-461, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01468-2
    DOI: 10.1007/s13198-021-01468-2
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