On the basis of laying weather detectors and tire sectors on the vehicle and traffic detectors along a sharply curved road section, some parameters related to weather and vehicle traveling are collected to calculate the adhesion coefficient and rolling resistance coefficient through artificial neural network. Then, the safe distance between vehicles is obtained, combining with velocity and road design parameters. At the same time, the actual distance between vehicles can be calculated by the velocity and the time traffic detectors recorded when a vehicle is approaching. If the actual distance is less than the safe distance, an alarm device will warn the vehicle to reduce its velocity in order to avoid a rear-end collision in adverse weather conditions.
Design of Rear-End Collision Warning System on Sharp Curved Highway Section under Adverse Weather Conditions
Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China
ICTIS 2013 ; 1305-1310
11.06.2013
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Rear-End Collision Risk Assessment in Adverse Weather Conditions
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