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Appl. Sci. 2017, 7(2), 129; doi:10.3390/app7020129

A Comprehensive Real-Time Traffic Map for Geographic Routing in VANETs

Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi 621, Taiwan
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Author to whom correspondence should be addressed.
Academic Editor: Christos Bouras
Received: 29 November 2016 / Revised: 16 January 2017 / Accepted: 23 January 2017 / Published: 26 January 2017
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Abstract

Vehicular Ad Hoc Networks (VANETs) have attracted a lot of attention during the last decade. VANETs can not only improve driving safety, but also convenience, and support most future Intelligent Transportation System (ITS). Due to the highly dynamic network topology of VANETs, many geographic routing protocols have been proposed and use real-time traffic information as an important metric to select a reliable forwarding path. However, most of the existing works do not describe how to gather real-time traffic. They either assume this information is already available, or can query an existing traffic center. Few studies have noticed this issue but the proposed solutions only consider a small region. In this paper, we propose a Comprehensive Real-Time Traffic Map (CRT Map) to collect wide-ranging real-time traffic information with low overhead. In the design of a CRT Map, the concept of Crowdsensing is adopted. Vehicles cooperatively gather traffic information and share it with each other to construct an overview of the whole road network traffic. In addition, we design a CRT Map Based Routing (CBR), which takes into account the connectivity of consecutive roads in routing decisions. Simulation results show that the CBR can achieve a lower end-to-end delay and a higher packet delivery ratio. View Full-Text
Keywords: VANETs; geographic routing protocol; real-time traffic information; crowdsensing VANETs; geographic routing protocol; real-time traffic information; crowdsensing
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Huang, C.-F.; Chan, Y.-F.; Hwang, R.-H. A Comprehensive Real-Time Traffic Map for Geographic Routing in VANETs. Appl. Sci. 2017, 7, 129.

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