Extraction of the Dynamic Vehicle Driver's Tendency Feature Based on Car-Following
Extraction of the Dynamic Vehicle Driver's Tendency Feature Based on Car-Following
- Neue Suche nach: Wang, Xiao-yuan
- Neue Suche nach: Zhang, Jing-lei
- Neue Suche nach: Liu, Jin
- Neue Suche nach: Cao, Kai
- Neue Suche nach: Gao, Song
- Neue Suche nach: Wang, Xiao-yuan
- Neue Suche nach: Zhang, Jing-lei
- Neue Suche nach: Liu, Jin
- Neue Suche nach: Cao, Kai
- Neue Suche nach: Gao, Song
The influence of the driver's physiological and psychological characteristics on traffic safety is mainly represented as driver's tendency. Previous research about the driver's tendency mostly focused on the influence on traffic safety and the driver's psychological characteristics from a relative static and macroscopic perspective. In this paper, the Multi-Sensor Real-time Information Gathering Systems and the car-following experiments are designed to collect dynamic information about driver's behavior, vehicle state, traffic environment, etc., to compute driver's tendency. The data is divided into groups and ran through BP Neural Networks to obtain the correct classification rate for estimation. The characteristics of driver's tendency are extracted from a great number of samples through the Discrete Particle Swarm Optimization Method.
Dokumentinformationen
Extraction of the Dynamic Vehicle Driver's Tendency Feature Based on Car-Following
The Twelfth COTA International Conference of Transportation Professionals ; 2012 ; Beijing, China
CICTP 2012 ; 2061-2071
2012-07-23
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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