Markov-based Emergency Message Reduction Scheme for Roadside Assistance

Hsin Hung Cho, Fan Hsun Tseng, Timothy K. Shih, Cong Zhang, Han Chieh Chao

研究成果: 雜誌貢獻期刊論文同行評審

4 引文 斯高帕斯(Scopus)


Currently, almost every family has at least one car; thus, vehicle density is increasing annually. However, road capacity is finite; consequently, traffic accident frequency may increase due to increasing vehicle density. Typically, car accidents result in traffic congestion because vehicles behind the accident are not aware of the event and continue to follow the front queue. To address this problem, some emergency services, such as emergency message broadcasting, have been proposed. However, not all drivers want to receive such messages because they intend to exit the route prior to the accident scene, which means that communication resources may be wasted. In this paper, we propose a prediction model to forecast vehicles behavior based on a Markov chain and identify which vehicles require the emergency message. In addition, the proposed model includes an efficient policy based on the shortest path for police cars and ambulances such that they can attend the accident scene quickly and relieve traffic congestion. Simulation results show that the proposed method reduces unnecessary message transmission and increases road utilization efficiently.

頁(從 - 到)859-867
期刊Mobile Networks and Applications
出版狀態已出版 - 1 10月 2017


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