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Author:

Chen, Xue-Mei (Chen, Xue-Mei.) | Gao, Li (Gao, Li.) | Wei, Zhong-Hua (Wei, Zhong-Hua.) | Li, Qian-Fei (Li, Qian-Fei.)

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EI Scopus PKU CSCD

Abstract:

Driver's factors are very important for the traffic safety. Questionnaire and BP neural network are used, the neural network structure with different hidden layer, neuron number and transfer function is established considering many parameters, such as age, gender, accumulative driving time, physiological conditions, etc. The optimal neural network structure is obtained to predict the traffic accident rate. The results show that the neural network is available for the prediction of accident rate and the driver subgroups with accident proneness are identified.

Keyword:

Highway accidents Neural networks Automobile drivers Accident prevention Transfer functions

Author Community:

  • [ 1 ] [Chen, Xue-Mei]School of Mechanical and vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China
  • [ 2 ] [Gao, Li]School of Mechanical and vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China
  • [ 3 ] [Wei, Zhong-Hua]Traffic Engineering Key Lab. of Beijing, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Li, Qian-Fei]School of Mechanical and vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2007

Issue: 7

Volume: 33

Page: 697-701

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: 10

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