Autonomic Navigation System Based on Predicted Traffic and VANETs

详细信息    查看全文

• 作者：Jyun-Yan Yang ; Li-Der Chou ; Li-Ming Tseng ; Yi-Ming Chen
• 关键词：Vehicle navigation ; Autonomous ; Car navigation ; Dynamic ; Traffic management
• 刊名：Wireless Personal Communications
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：92
• 期：2
• 页码：515-546
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks;
• 出版者：Springer US
• ISSN：1572-834X
• 卷排序：92

文摘

To avoid an expected traffic jam, drivers make detours based on limited information; however, the majority following the alike routes may result in an unexpected congestion. Conventional navigation approaches are unable to respond to the unexpected congestion because these approaches do not consider the routes taken by other vehicles. Navigation systems that utilize global traffic information can improve gas consumption, CO₂ emissions and travel time. Therefore, in this paper, the authors propose an autonomic navigation system (ANS) operating over vehicular ad-hoc networks (VANETs). The proposed ANS adopts a hierarchical algorithm to plan vehicle routes. The proposed ANS imitates the human nervous system when managing the navigation system, in which vehicles monitor traffic via VANETs. Moreover, this paper proposes a time-dependent routing algorithm that uses a novel traffic prediction method based on the routes of vehicles. This paper adopts EstiNet as simulator tool that dominates hundreds or thousands of VANET-based vehicles routing in two maps, Manhattan area, and Taipei city. The results show that the proposed ANS improves the average speed by 60.02 % when compared with the shortest path first (SPF) algorithm and by 15.49 % when compared with the distributed method of a traffic simulation in the Manhattan area. The proposed ANS also improves the average speed by 30.5 % when compared with the SPF algorithm and by 15.8 % when compared with the distributed method of a traffic simulation in the Taipei area. Furthermore, to emulate real environments, there is a scenario in which only a portion of the vehicles complies with the proposed ANS.