Investigation of speed estimation using single loop detectors.
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2008-05-15
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Abstract:The ability to collect or estimate accurate speed information is of great importance to a large number of
Intelligent Transportation Systems (ITS) applications. Estimating speeds from the widely used single
inductive loop sensor has been a difficult, yet important challenge for transportation engineers. Based on
empirical evidence observed from the sensor data from two metropolitan regions in Northern Virginia and
California, this research effort developed a Kalman filter model to perform speed estimation for congested
traffic. Taking advantage of the coexistence of dual loop and single loop stations in typical freeway
management systems, a calibration procedure was proposed for seeding and initiating the algorithm.
Empirical evaluation showed that the proposed algorithm can produce accurate speed estimates (on the order
of 1-3 miles/hour error) under congested traffic conditions.
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