An Adaptive Algorithm for Freeway Speed Estimation with Single-Loop Measurements
نویسنده
چکیده
Accurate, real-time traffic speed data are important inputs to successful freeway traffic management systems. Unfortunately, vehicle speeds cannot be directly measured by single-loop detectors, which are the most common detectors available in current freeway infrastructures. Algorithms are required to estimate speed using single-loop measurements. In this paper, we present a two-step speed estimation algorithm: in the first step, single loop measurements are filtered to screen out intervals containing long vehicles; and in the second step, space-mean speed is calculated using measurements for intervals containing only passenger cars. Twenty-four hour data that contain both free flow conditions and moderately congested conditions are used to test the algorithm. Speeds estimated by the proposed method are very close to the speeds observed by the corresponding dual-loop detector. Compared to the commonly adopted speed estimation algorithm with unfiltered data, the proposed method improves speed estimation accuracy significantly. Keyword: speed, filter, vehicle length, single loop
منابع مشابه
The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
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