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Analysis and improvement of vehicle information sharing networks

Author

Listed:
  • Gong, Hang
  • He, Kun
  • Qu, Yingchun
  • Wang, Pu

Abstract

Based on large-scale mobile phone data, mobility demand was estimated and locations of vehicles were inferred in the Boston area. Using the spatial distribution of vehicles, we analyze the vehicle information sharing network generated by the vehicle-to-vehicle (V2V) communications. Although a giant vehicle cluster is observed, the coverage and the efficiency of the information sharing network remain limited. Consequently, we propose a method to extend the information sharing network’s coverage by adding long-range connections between targeted vehicle clusters. Furthermore, we employ the optimal design strategy discovered in square lattice to improve the efficiency of the vehicle information sharing network.

Suggested Citation

  • Gong, Hang & He, Kun & Qu, Yingchun & Wang, Pu, 2016. "Analysis and improvement of vehicle information sharing networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 106-112.
    • Handle: RePEc:eee:phsmap:v:452:y:2016:i:c:p:106-112
    DOI: 10.1016/j.physa.2016.01.062
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    References listed on IDEAS

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    1. Wang, Kai & Zhang, Yifeng & Zhou, Siyuan & Pei, Wenjiang & Wang, Shaoping & Li, Tao, 2011. "Optimal routing strategy based on the minimum information path," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2593-2600.
    2. Jon M. Kleinberg, 2000. "Navigation in a small world," Nature, Nature, vol. 406(6798), pages 845-845, August.
    3. Hong, Chen, 2015. "Effective usage of global dynamic information for network traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 242-247.
    4. Xiaolei Ma & Haiyang Yu & Yunpeng Wang & Yinhai Wang, 2015. "Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    5. Huang, Wei & Chen, Shengyong & Wang, Wanliang, 2014. "Navigation in spatial networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 132-154.
    6. He, Kun & Xu, Zhongzhi & Wang, Pu, 2015. "A hybrid routing model for mitigating congestion in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 1-17.
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    Cited by:

    1. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    2. Ding, Rui & Ujang, Norsidah & Hamid, Hussain bin & Manan, Mohd Shahrudin Abd & He, Yuou & Li, Rong & Wu, Jianjun, 2018. "Detecting the urban traffic network structure dynamics through the growth and analysis of multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 800-817.
    3. Davis, L.C., 2017. "Dynamic origin-to-destination routing of wirelessly connected, autonomous vehicles on a congested network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 93-102.

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