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Author:

Xu, Zhi (Xu, Zhi.) | Yang, Xiao-Kuan (Yang, Xiao-Kuan.) | Zhao, Xiao-Hua (Zhao, Xiao-Hua.) | Li, Ling-Jie (Li, Ling-Jie.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

Scenario simulation is employed to create a driving environment in the emergency evacuation and the questionnaire investigation and the Miriam ECG are used to verify the validity of the driving environment in the emergency evacuation from subjective and objective aspects. Gray-correlation Analysis is undertaken to determine which factors have more impact on the acceleration of the following car. Acceleration of the following car is set as the mother factor series and the speed of the following car, speed of the front car, speed difference between vehicles, headway between vehicles, acceleration of the front car are set as the sub-factor series. Finally acceleration of the front car, speed difference between vehicles, speed of the following car are determined as three most important factors. BP neural network is designed and the three factors mentioned above are selected as input variables and the acceleration of the following car is selected as output variable. Simulation of the BP neural network with data gathered from driving simulator reveals that BP neural network has a high precision in the prediction of the car-following model.

Keyword:

Acceleration Speed Neural networks Vehicles Automobile drivers

Author Community:

  • [ 1 ] [Xu, Zhi]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Yang, Xiao-Kuan]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Zhao, Xiao-Hua]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Li, Ling-Jie]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2011

Issue: 6

Volume: 37

Page: 882-887

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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