Title :
Cooperative Collision Warning through mobility and probability prediction
Author :
Yan, Gongjun ; Yang, Weiming ; Weigle, Michele C. ; Olariu, Stephan ; Rawat, Danda
Author_Institution :
Comput. Sci. Dept., Old Dominion Univ., Norfolk, VA, USA
Abstract :
The past decade has witnessed the confluence of Intelligent Transportation Systems (ITS) and Vehicular Ad hoc Networks (VANET) that promises to revolutionize incident detection and the timely dissemination of traffic-related information to the various interested parties. One of the key components is expected to be a Cooperative Collision Warning System (CCWS). Our main contribution is to derive analytical expressions for key CCWS metrics that rely on mobility information exchanged by various players. The feasibility of CCWS has been demonstrated in previous work; this paper analyzes the mobility parameters and derives the conditional probability of a collision. We begin by proposing a set of fundamental parameters for CCWS: conditional probability of collision, headway distance, driver reaction time, relative velocity and acceleration. Preliminary simulation results have demonstrated the effectiveness of our analytical derivations.
Keywords :
ad hoc networks; automated highways; collision avoidance; information dissemination; probability; road safety; CCWS metrics; VANET; collision conditional probability; cooperative collision warning; driver reaction time; headway distance; intelligent transportation systems; mobility information; mobility prediction; probability prediction; relative acceleration; relative velocity; traffic related information dissemination; vehicular ad hoc networks; Acceleration; Ad hoc networks; Alarm systems; Analytical models; Information analysis; Intelligent networks; Intelligent transportation systems; Intelligent vehicles; Road accidents; Telecommunication traffic;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2010 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7866-8
DOI :
10.1109/IVS.2010.5547990