原文传递 Increasing Accuracy of Vehicle Detection from Conventional Vehicle Detectors-Counts, Speeds, Classification, and Travel Time.
题名: Increasing Accuracy of Vehicle Detection from Conventional Vehicle Detectors-Counts, Speeds, Classification, and Travel Time.
作者: Coifman, B.; Wei, H.; Wu, L.
关键词: Acceleration; Accuracy; Counting Methods; Data Collection; Detection; Loop Detectors; Speed; Traffic Congestion; Transportation Planning; Travel Time; Vehicle Classification; Vehicle Length
摘要: Vehicle classification is an important traffic parameter for transportation planning and infrastructure management. Length-based vehicle classification from dual loop detectors is among the lowest cost technologies commonly used for collecting these data. Like many vehicle classification technologies, the dual loop approach works well in free flow traffic. Effective vehicle lengths are measured from the quotient of the detector dwell time and vehicle traversal time between the paired loops. This approach implicitly assumes that vehicle acceleration is negligible, but unfortunately at low speeds this assumption is invalid and length-based classification performance degrades in congestion. To addresses this problem, we seek a solution that relies strictly on the measured effective vehicle length and measured speed. We analytically evaluate the feasible range of true effective vehicle lengths that could underlie a given combination of measured effective vehicle length, measured speed, and unobserved acceleration at a dual loop detector.
报告类型: 科技报告
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