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A traffic congestion aware vehicle-to-vehicle communication framework based on Voronoi diagram and information granularity

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Abstract

Vehicle-to-Vehicle (V2 V) communication opens up new possibilities for the traffic surveillance because of its high accuracy and real-time performance on detecting and avoiding traffic congestion. This work presents a traffic congestion aware V2 V communication framework based on Voronoi diagram and information granularity. Voronoi diagram is used to divide the map into different regions that provide the basis for the proposed V2 V communication model. Then the generation and propagation mechanisms of information about traffic congestion including the intersection congestion and the incident congestion are described. In the proposed V2 V communication, the combination of carry-and-forward strategy and reverse relay strategy is adopted to optimize the information propagation. After analyzing the influence of PoV, which is the ratio of vehicles with the ability of V2 V communication to all vehicles, congestion detection based on information granularity and congestion avoidance based on PoV are also proposed separately. Finally, the performance of such framework is validated by comparison with existing routing protocols and the common approaches adopted in existing maps. This novel V2 V communication framework used in the field of traffic surveillance can effectively increase the ability of detecting and avoiding traffic congestion.

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Acknowledgments

This work is supported by CERNET Innovation Project (Grant No. NGII20151205).

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, Shanghai, China

    Gang Li & Bin He

  2. Automotive College, Tongji University, Shanghai, China

    Aimin Du

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  1. Gang Li
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  2. Bin He
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  3. Aimin Du
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Correspondence to Aimin Du.

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Li, G., He, B. & Du, A. A traffic congestion aware vehicle-to-vehicle communication framework based on Voronoi diagram and information granularity. Peer-to-Peer Netw. Appl. 11, 124–138 (2018). https://doi.org/10.1007/s12083-016-0491-y

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  • DOI: https://doi.org/10.1007/s12083-016-0491-y

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