Authors: Jun Liang, Long Chen, Xiaobo Chen
Addresses: School of Computer Science and Telecommunication Engineering, JiangSu University, Zhenjiang 212013, China. ' School of Automobile and Traffic Engineering, JiangSu University, Zhenjiang 212013, China. ' School of Computer Science and Telecommunication Engineering, JiangSu University, Zhenjiang 212013, China
Abstract: The measurement of the distance between vehicles is the only factor in traditional car rear-end alarm system. To address the above problem, this paper proposes an alarm model based on Multi-Agent Systems (MAS) and driving behaviour. It consists of four different types of agents that can collaborate through a communications protocol on the basis of the extended KQML. The Bayes decision theory is adopted to calculate the probability of collision and prevent its occurence realtime. Both autonomy and reliability are enhanced in the proposed system. The effectiveness and robustness of the model have been confirmed by simulated experiments.
Keywords: multi-agent systems; MAS; driving behaviour; Bayes decision; KQML; knowledge query and manipulation language; car rear-end warning; agent-based systems; automotive alarm systems; automotive warning systems; vehicle safety; automobile industry; collision prevention; collision avoidance; vehicle crashes; road accidents.
International Journal of Computer Applications in Technology, 2010 Vol.39 No.4, pp.207 - 212
Accepted: 03 Jun 2010
Published online: 12 Oct 2010 *