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Cited 9 time in webofscience Cited 15 time in scopus
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Assessing the performance of SpeedInfo radar traffic sensors

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dc.contributor.authorKim, Seoungbum-
dc.contributor.authorCoifman, Benjamin-
dc.date.accessioned2022-12-26T19:48:44Z-
dc.date.available2022-12-26T19:48:44Z-
dc.date.issued2017-
dc.identifier.issn1547-2450-
dc.identifier.issn1547-2442-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/15046-
dc.description.abstractTraffic speed is a crucial input for real-time traffic management applications. Operating agencies typically deploy their own sensors to collect the measurements, e.g., loop detectors. Recently, SpeedInfo emerged with a different paradigm for traffic speed collection: instead of selling hardware to operating agencies, at each link the company deploys its own Doppler radar in a self-contained wireless unit to measure traffic speeds and then sells the speed data. This study uses well-tuned loop detector-based speed measurements to evaluate 15 of the Doppler radar sensors over several months while the two traffic data collection systems were operating concurrently. The extended study period includes potentially challenging and transient conditions for the radar sensors: both recurrent (rush hour congestion and late night low flow) and nonrecurrent (incidents and precipitation). The analysis took a broad overview, comparing speed measurements from the radar sensors against the concurrent loop detector data and then explicitly looked for any anomalous pattern in the radar data such as latency and system outages. The work found the radar measurements are generally good, but also identified several points that should be considered before deployment, including latency, different biases in free flow and congestion, vulnerability to precipitation, and sensitivity to mounting angle.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherTAYLOR & FRANCIS INC-
dc.titleAssessing the performance of SpeedInfo radar traffic sensors-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1080/15472450.2016.1273779-
dc.identifier.scopusid2-s2.0-85012307822-
dc.identifier.wosid000401775400002-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, v.21, no.3, pp 179 - 189-
dc.citation.titleJOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS-
dc.citation.volume21-
dc.citation.number3-
dc.citation.startPage179-
dc.citation.endPage189-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaTransportation-
dc.relation.journalWebOfScienceCategoryTransportation-
dc.relation.journalWebOfScienceCategoryTransportation Science & Technology-
dc.subject.keywordPlusFREEWAY LOOP DETECTORS-
dc.subject.keywordPlusERRORS-
dc.subject.keywordAuthorfreeway traffic-
dc.subject.keywordAuthorperformance evaluation-
dc.subject.keywordAuthorSpeedInfo-
dc.subject.keywordAuthorspeed measurement-
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