DocumentCode
2122750
Title
Enhancing Automatic Incident Detection Techniques Through Vehicle To Infrastructure Communication
Author
Abuelela, Mahmoud ; Olariu, Stephan ; Yan, Gongjun
Author_Institution
Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
447
Lastpage
452
Abstract
One of the fundamental requirements of a traffic management system is the ability to determine when an incident has occurred so that proper responses can be initiated. Automatic incident detection (AID) has been considered a method for quickly detecting potential incidents on the road. Although vehicular ad hoc networks (VANETs) started mainly for safety applications, surprisingly a very few work have been done in VANETs for automatic incident detection while most of the research went for developing routing protocols and privacy techniques. In this paper, we introduce a novel incident detection technique for non dense traffic flow by taking advantage of communication between cars and some roadside infrastructure installed on the road every mile or so. The proposed technique can provide a great enhancement to the existing AID techniques specially under sparse traffic where most of them fail to detect non blocking incidents.
Keywords
ad hoc networks; automobiles; mobile radio; road traffic; road vehicles; routing protocols; VANET; automatic incident detection technique; car traffic flow; roadside infrastructure; routing protocol; traffic management system; vehicle-to-infrastructure communication; vehicle-to-vehicle communication; vehicular ad hoc network; Ad hoc networks; Event detection; Intelligent transportation systems; Privacy; Road accidents; Routing protocols; Safety; Telecommunication traffic; Vehicle detection; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Transportation Systems, 2008. ITSC 2008. 11th International IEEE Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2111-4
Electronic_ISBN
978-1-4244-2112-1
Type
conf
DOI
10.1109/ITSC.2008.4732687
Filename
4732687
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