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Markov-based Emergency Message Reduction Scheme for Roadside Assistance

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Abstract

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.

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Acknowledgments

This research was partly funded by the National Science Council of the R.O.C. under grants MOST 104-2221-E-197- 014 - and 105-2221-E-197 -010 -MY2.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China

    Hsin-Hung Cho, Fan-Hsun Tseng & Timothy K. Shih

  2. School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China

    Cong Zhang & Han-Chieh Chao

  3. Department of Electrical Engineering, National Dong Hwa University, Hualien, Taiwan, Republic of China

    Han-Chieh Chao

  4. College of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Han-Chieh Chao

  5. Department of Computer Science and Information Engineering, National Ilan University, Yilan, Taiwan, Republic of China

    Han-Chieh Chao

  6. School of Information Science and Engineering, Fujian University of Technology, Fujian, China

    Han-Chieh Chao

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  1. Hsin-Hung Cho
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  2. Fan-Hsun Tseng
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  3. Timothy K. Shih
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  4. Cong Zhang
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  5. Han-Chieh Chao
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Correspondence to Han-Chieh Chao.

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Cho, HH., Tseng, FH., Shih, T.K. et al. Markov-based Emergency Message Reduction Scheme for Roadside Assistance. Mobile Netw Appl 22, 859–867 (2017). https://doi.org/10.1007/s11036-017-0852-7

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  • DOI: https://doi.org/10.1007/s11036-017-0852-7

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