Abstract
Most of the existing algorithms of vehicle rear-end collision have poor adaptive, high false alarm and missed alarm rates. A two-level early warning model based on logic algorithm of safe distance is discussed. The influence of road conditions, driver status and vehicle performance on the warning distance of rear-end collision in the driving process is analyzed. And for different driving conditions, a warning algorithm of vehicle rear-end collision based on neural network with adaptive threshold which can adapt to different status of the three main elements, human-vehicle-road is proposed. Also the comparison of the warning distance whether using adaptive strategies for the rear-end collision algorithm through changing the real-time status of human-vehicle-road is presented. The result of the simulation shows that the algorithm proposed is self-adaptive to the warning distance and region, and the feasibility of the algorithm is verified.
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© 2011 Springer-Verlag Berlin Heidelberg
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Wei, Z., Xiang, S., Xuan, D., Xu, L. (2011). An Adaptive Vehicle Rear-End Collision Warning Algorithm Based on Neural Network. In: Zhu, M. (eds) Information and Management Engineering. ICCIC 2011. Communications in Computer and Information Science, vol 236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24097-3_46
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DOI: https://doi.org/10.1007/978-3-642-24097-3_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24096-6
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