DocumentCode :
1113297
Title :
Anonymous Vehicle Reidentification Using Heterogeneous Detection Systems
Author :
Oh, Cheol ; Ritchie, Stephen G. ; Jeng, Shin-Ting
Author_Institution :
Hanyang Univ., Ansan
Volume :
8
Issue :
3
fYear :
2007
Firstpage :
460
Lastpage :
469
Abstract :
An innovative feature of this paper is the demonstration of the feasibility of real-time vehicle reidentification algorithm development at a signalized intersection, where different traffic detection technologies were employed at upstream and downstream locations. Previous research by the authors on vehicle reidentification has utilized the same traffic sensors (e.g., conventional square inductive loops) and detectors (e.g., high-speed scanning detector cards) at both locations. In this paper, an opportunity arose for the first time to collect a downstream data set from a temporary installation of a prototype innovative inductive loop sensor known as a ldquobladerdquo sensor in conjunction with conventional inductive loops upstream. At both locations, advanced high-speed scanning detector cards were used. Although the number of vehicles for which data could be collected was small, encouraging results were obtained for vehicle reidentification performance in this system of mixed traffic detection technologies. In future large-scale applications of vehicle reidentification approaches for real-time traffic performance measurement, management, and control, it would be most beneficial and practical if heterogeneous and homogeneous detection systems could be supported. This initial paper yielded many useful insights about this important issue and demonstrated on a small scale the feasibility of vehicle reidentification in a system with heterogeneous detection technologies.
Keywords :
genetic algorithms; road vehicles; sensors; traffic engineering computing; anonymous vehicle reidentification; blade sensor; genetic algorithm; heterogeneous detection systems; inductive loop sensor; mixed traffic detection technologies; real-time vehicle reidentification algorithm; scanning detector cards; Automotive engineering; Control systems; Detectors; Large-scale systems; Measurement; Privacy; Prototypes; Real time systems; Transportation; Vehicle detection; Genetic algorithm (GA); lexicographic optimization; travel time estimation; vehicle feature; vehicle reidentification;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2007.899720
Filename :
4298907
Link To Document :
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