Vehicular ad-hoc networks sampling protocols for traffic monitoring and incident detection in intelligent transportation systems

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.