Mobile Networks and Applications

, Volume 22, Issue 5, pp 859–867 | Cite as

Markov-based Emergency Message Reduction Scheme for Roadside Assistance

  • Hsin-Hung Cho
  • Fan-Hsun Tseng
  • Timothy K. Shih
  • Cong Zhang
  • Han-Chieh Chao
Article
  • 155 Downloads

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.

Keywords

VANET Emergency service Markov chain Prediction model 

Notes

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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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Computer Science and Information EngineeringNational Central UniversityTaoyuanRepublic of China
  2. 2.School of Mathematics and Computer ScienceWuhan Polytechnic UniversityWuhanChina
  3. 3.Department of Electrical EngineeringNational Dong Hwa UniversityHualienRepublic of China
  4. 4.College of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingChina
  5. 5.Department of Computer Science and Information EngineeringNational Ilan UniversityYilanRepublic of China
  6. 6.School of Information Science and EngineeringFujian University of TechnologyFujianChina

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