DocumentCode :
3066444
Title :
Enhancing Automatic Incident Detection Using Vehicular Communications
Author :
Abuelela, Mahmoud ; Olariu, Stephan ; Cetin, Mecit ; Rawat, Danda
Author_Institution :
Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA, USA
fYear :
2009
fDate :
20-23 Sept. 2009
Firstpage :
1
Lastpage :
5
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. Most of the existing automatic incident detection techniques suffer from many limitations including their inability to detect incidents under non dense traffic conditions and generation of many false positive alarms. In this paper, we introduce a novel Bayesian-based approach to enhance the performance of existing techniques specially under non-dense traffic flow through vehicle to readside communications. The proposed technique also offers zero false positive alarms under most situations and can be integrated with any of the current techniques.
Keywords :
Bayes methods; mobile communication; road vehicles; traffic engineering computing; vehicles; Bayesian-based approach; automatic incident detection; non-dense traffic flow; readside communications; traffic management system; vehicular communications; Cameras; Cellular phones; Detectors; Road accidents; Telecommunication traffic; Time measurement; Traffic control; Vehicles; Velocity measurement; Volume measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th
Conference_Location :
Anchorage, AK
ISSN :
1090-3038
Print_ISBN :
978-1-4244-2514-3
Electronic_ISBN :
1090-3038
Type :
conf
DOI :
10.1109/VETECF.2009.5378790
Filename :
5378790
Link To Document :
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