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An Adaptive Vehicle Rear-End Collision Warning Algorithm Based on Neural Network

  • Zhou Wei
  • Song Xiang
  • Dong Xuan
  • Li Xu
Part of the Communications in Computer and Information Science book series (CCIS, volume 236)

Abstract

Most of the existing algorithms of vehicle rear-end collision have poor adaptive, high false alarm and missed alarm rates. A two-level early warning model based on logic algorithm of safe distance is discussed. The influence of road conditions, driver status and vehicle performance on the warning distance of rear-end collision in the driving process is analyzed. And for different driving conditions, a warning algorithm of vehicle rear-end collision based on neural network with adaptive threshold which can adapt to different status of the three main elements, human-vehicle-road is proposed. Also the comparison of the warning distance whether using adaptive strategies for the rear-end collision algorithm through changing the real-time status of human-vehicle-road is presented. The result of the simulation shows that the algorithm proposed is self-adaptive to the warning distance and region, and the feasibility of the algorithm is verified.

Keywords

rear-end collision adaptive warning algorithm nerual network 

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References

  1. 1.
    Ministry of Public Security Traffic Management Bureau. PRC Road Accidents Statistical Report (2009) p. 8 Ministry of Public Security Traffic Management Research Institute, Wuxi (2010)Google Scholar
  2. 2.
    Shanghai Municipal Education Commission. Modern Automotive Safety Technology. Shanghai Jiaotong University Press, Shanghai (2006)Google Scholar
  3. 3.
    Chang, T.-H., Hsu, C.-S., Wang, C., Yang, L.-K.: Onboard Measurement and Warning Module for Irregular Vehicle Behavior. IEEE Transactions on Intelligent Transportation Systems 9(3), 501–513 (2008)CrossRefGoogle Scholar
  4. 4.
    Yoshida, H., Awano, S., Nagai, M., Kamada, T.: Target Following Brake Control for Collision Avoidance Assist of Active Interface Vehicle. In: SICE-ICASE International Joint Conference 2006, Bexco, Busan, Korea, October 18-21, pp. 4436–4439 (2006)Google Scholar
  5. 5.
    Lee, K., Peng, H.: Evaluation of automotive forward collision warning and collision avoidance algorithms. Vehicle System Dynamics 10(43), 735–751 (2005)CrossRefGoogle Scholar
  6. 6.
    Li, X.x., Li, B.c., Hou, D.z., Chen, G.w.: Basic study of rear-end collis ion warning system. China Journal of Highway and Transport 14(3), 93–95 (2001)Google Scholar
  7. 7.
    Wang, W.q., Wang, W.h., Zhong, Y.g., Yi, S.p.: Car-following safe distance control algorithm and implemen tat ion based on fuzzy inference. Journal of Traffic and Transportation Engineering 3(1), 72–75 (2003)Google Scholar
  8. 8.
    Xu, J., Du, W., Sun, H.: Safety distance about car-following. Journal of Traffic and Transportation Engineering 2(1), 101–104 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Zhou Wei
    • 1
  • Song Xiang
    • 2
  • Dong Xuan
    • 1
  • Li Xu
    • 2
  1. 1.Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Communication, PRCResearch Institute of Highway Ministry of CommunicationsChina
  2. 2.School of Instrument Science and EngineeringSoutheast UniversityNanJingChina

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