Vehicular Ad-Hoc Networks sampling protocols for traffic monitoring and incident detection in Intelligent Transportation Systems. (July 2015)

• Record Type: Journal Article
• Authors: Baiocchi, Andrea; Cuomo, Francesca; De Felice, Mario; Fusco, Gaetano
• Is Part Of: Transportation research. Volume 56(2015)
• Page Start: 177
• Page End: 194
• Publication Date: 2015-07
• Subjects: Vehicular traffic monitoring -- VANET -- Incident detection -- Distributed algorithms -- FCD collection -- Multi-hop communications; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2015.03.041
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: We define distributed, autonomous FCD collection protocols based on VANET. We show accurate real time speed estimation based on FCD sampling through VANET. We run simulations on a real highway driven by vehicular traffic from real GPS traces. We devise an incident detection algorithm based on standard accuracy GPS positions. Abstract: Vehicular Ad-Hoc Networks (VANETs) are an emerging technology soon to be brought to everyday life. Many Intelligent Transport Systems (ITS) services that are nowadays performed with expensive infrastructure, like reliable traffic monitoring and car accident detection, can be enhanced and even entirely provided through this technology. In this paper, we propose and assess how to use VANETs for collecting vehicular traffic measurements. We provide two VANET sampling protocols, named SAME and TOME, and we design and implement an application for one of them, to perform real time incident detection. The proposed framework is validated through simulations of both vehicular micro-mobility and communications on the 68 km highway that surrounds Rome, Italy. Vehicular traffic is generated based on a large real GPS traces set measured on the same highway, involving about ten thousand vehicles over many days. We show that the sampling monitoring protocol, SAME, collects data in few seconds with relative errors less than 10%, whereas the exhaustive protocol TOME allows almost fully accurate estimates within few tens of seconds. We also investigate the effect of a limited deployment of the VANET technology on board of vehicles. Both traffic monitoring and incident detection are shown to still be feasible with just 50% of equipped vehicles.