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Online travel time estimation without vehicle identification Lucas, David E ; Mirchandani, Pitu B ; Verma, Nitascha

By: Contributor(s): Publication details: Transportation Research Record, 2004Description: nr 1867, s. 193-201Subject(s): Bibl.nr: VTI P8167:1867; VTI P8169:2004Location: Abstract: A new approach is presented to the estimation of travel times (in real time) on arterials on the basis of second-by-second data from detectors that count vehicles. Unlike most approaches, which attempt to track individual vehicles as they move throughout the network, the proposed approach tracks clusters, or platoons, of vehicles. This approach offers several advantages over existing methods and provides good travel time estimates for arterial networks. Although other methods of estimating travel times have varying degrees of success, they each suffer from limitations ranging from processing, equipment, and infrastructure requirements to personnel cost for probe vehicles, sociopolitical issues of surveillance, and the perceived loss of privacy. The proposed method attempts to overcome some of these limitations. Because existing detection and controller infrastructure is used, additional equipment is not required. Second-by-second detector data are used to identify platoons of vehicles but not individual vehicles. The platoons, and not individual vehicles, are then tracked as they travel from upstream detectors to downstream detectors on a route segment, producing travel time estimates for this segment. In addition, since the proposed method captures the aggregate flow of vehicles, it should better measure the central tendencies of the driver population and current traffic conditions as reflected by travel times at the prevailing congestion levels.
Item type: Reports, conferences, monographs
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Statens väg- och transportforskningsinstitut Available

A new approach is presented to the estimation of travel times (in real time) on arterials on the basis of second-by-second data from detectors that count vehicles. Unlike most approaches, which attempt to track individual vehicles as they move throughout the network, the proposed approach tracks clusters, or platoons, of vehicles. This approach offers several advantages over existing methods and provides good travel time estimates for arterial networks. Although other methods of estimating travel times have varying degrees of success, they each suffer from limitations ranging from processing, equipment, and infrastructure requirements to personnel cost for probe vehicles, sociopolitical issues of surveillance, and the perceived loss of privacy. The proposed method attempts to overcome some of these limitations. Because existing detection and controller infrastructure is used, additional equipment is not required. Second-by-second detector data are used to identify platoons of vehicles but not individual vehicles. The platoons, and not individual vehicles, are then tracked as they travel from upstream detectors to downstream detectors on a route segment, producing travel time estimates for this segment. In addition, since the proposed method captures the aggregate flow of vehicles, it should better measure the central tendencies of the driver population and current traffic conditions as reflected by travel times at the prevailing congestion levels.

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