Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 오철 | - |
dc.date.accessioned | 2019-07-01T06:20:49Z | - |
dc.date.available | 2019-07-01T06:20:49Z | - |
dc.date.issued | 2007-09 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v. 8, No. 3, Page. 460-469 | en_US |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | https://ieeexplore.ieee.org/document/4298907 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/106964 | - |
dc.description.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 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. | en_US |
dc.description.sponsorship | This work was performed as part of the California Partners for Advanced Highways and Transit (PATH) program of the University of California in cooperation with the Business, Transportation, and Housing Agency, California Department of Transportation, and FHWA, U.S. Department of Transportation. The content of this paper reflects the view of the authors, who are responsible for the facts and the accuracy of the data presented. The contents do not necessarily reflect the official views or polices of the state of California. This paper does not constitute a standard, specification, or regulation. The authors gratefully acknowledge the collaboration and assistance of S. Hilliard, Inductive Signature Technologies, Inc., in conducting this study, especially in providing the prototype blade sensors and portable data collection equipment. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_US |
dc.subject | genetic algorithm (GA) | en_US |
dc.subject | lexicographic optimization | en_US |
dc.subject | travel time estimation | en_US |
dc.subject | vehicle feature | en_US |
dc.subject | vehicle reidentification | en_US |
dc.title | Anonymous Vehicle Reidentification using Heterogeneous Detection Systems | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/TITS.2007.899720 | - |
dc.relation.journal | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | - |
dc.contributor.googleauthor | Oh, Cheol | - |
dc.contributor.googleauthor | Ritchie, Stephen G. | - |
dc.contributor.googleauthor | Jeng, Shin-Ting | - |
dc.relation.code | 2007214110 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING | - |
dc.identifier.pid | cheolo | - |
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