4.7 Article

Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network

期刊

INFORMATION SCIENCES
卷 408, 期 -, 页码 100-114

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2017.04.042

关键词

Intelligent transportation system; Parking navigation; Wireless sensor network; Information potential field

资金

  1. West Virginia Higher Education Policy Commission [FRT2W762W]
  2. China Postdoctoral Science Foundation [2013M542370]
  3. Specialized Research Fund for the Doctoral Program of Higher Education of China [20136118120010]
  4. NSFC Grant [11301414, 11226173, 51409213]
  5. Beilin District High-tech Plan in Xi'an of China [GX1504]
  6. Xi'an science and technology project [CXY1440(6)]
  7. Scientific Research Program - Shaanxi Provincial Education Department [2013JK1139]
  8. Shaanxi Province Hundred Talents Program
  9. Natural Science Foundation of China [61272509]
  10. Research Fund for the Doctoral Program of Higher Education [20136118110002]
  11. Natural Science Foundation of Shaanxi Province [2016JM6058]
  12. Shaanxi Scientific research [2014k07-11]

向作者/读者索取更多资源

Wireless sensor networks can support building and transportation system automation in numerous ways. An emerging application is to guide drivers to promptly locate vacant parking spaces in large parking structures during peak hours. This paper proposes efficient parking navigation via a continuous information potential field and gradient ascent method. Our theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation. The empirical study demonstrates that the proposed algorithm performs more efficiently than existing algorithms. (C) 2017 Elsevier Inc. All rights reserved.

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