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

被引:185
作者
Wei, Wei [1 ]
Song, Houbing [2 ]
Li, Wei [3 ]
Shen, Peiyi [4 ]
Vasilakos, Athanasios [5 ]
机构
[1] Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Peoples R China
[2] West Virginia Univ, Dept Elect & Comp Engn, Montgomery, WV 25136 USA
[3] Univ Sydney, Sch Informat Technol, Ctr Distributed & High Performance Comp, Sydney, NSW 2006, Australia
[4] Xidian Univ, Natl Sch Software, Xian 710071, Peoples R China
[5] Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, Lulea, Sweden
基金
高等学校博士学科点专项科研基金; 中国博士后科学基金;
关键词
Intelligent transportation system; Parking navigation; Wireless sensor network; Information potential field;
D O I
10.1016/j.ins.2017.04.042
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:100 / 114
页数:15
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