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.
| Original language | English |
|---|---|
| Pages (from-to) | 697-701 |
| Number of pages | 5 |
| Journal | Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology |
| Volume | 33 |
| Issue number | 7 |
| Publication status | Published - Jul 2007 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Accident rate
- Driver
- Neural network
- Traffic accident
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