Anonymous vehicle reidentification using heterogeneous detection systems

被引:21
|
作者
Oh, Cheol [1 ]
Ritchie, Stephen G.
Jeng, Shin-Ting
机构
[1] Hanyang Univ, Dept Transportat Syst Engn, Ansan 426791, South Korea
[2] Univ Calif Irvine, Inst Transport Studies, Dept Syst Engn, Irvine, CA 92697 USA
关键词
genetic algorithm (GA); lexicographic optimization; travel time estimation; vehicle feature; vehicle reidentification;
D O I
10.1109/TITS.2007.899720
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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 "blade" 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.
引用
收藏
页码:460 / 469
页数:10
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