Calibration of automatic performance measures – speed and volume data: volume 2, evaluation of the accuracy of approach volume counts and speeds collected by microwave sensors.
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2016-05-01
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Abstract:This study evaluated the accuracy of approach volumes and free flow approach speeds collected by the Wavetronix ; SmartSensor Advance sensor for the Signal Performance Metrics system of the Utah Department of Transportation (UDOT), ; using the field data collected by JAMAR counter boards for free flow approach volumes and a TruCam LiDAR gun for approach ; speeds. The Advance sensor is primarily designed for dilemma zone reduction. It does not have the capability to differentiate ; vehicles between lanes, but the Advance sensor currently used has a detection range of up to 600 ft. and has the capability to ; track vehicles approaching the intersection. UDOT wanted to use this capability to get added values from their investment in the ; Advance sensors. The approach volume accuracy was analyzed with three factors: sensor position, number of approach lanes, and ; approach volume level. The results showed that the high accuracy is achieved when the number of approach lanes is low, or ; closer to one-lane, and the approach volume level is low. The overall range of accuracy for the approach volume counts was ; found to range from approximately 77.8% (22.2% undercount) to 105.7% (5.7% overcount). The accuracy of approach speeds ; was analyzed with two factors: the number of lanes and offset position of the lanes relative to the location of the speed gun. The ; offset position was first tested and found not to affect the accuracy of approach speeds. In general, the difference in means was ; approximately ±2 mph and was not considered practically significant. The 85th percentile speed for sites with more than 50 ; samples were then evaluated. For these sites, the average difference in 85th percentile speed was -0.43 mph, the biggest negative ; difference being -1.6 mph, and the biggest positive difference being 1.5 mph. A Bootstrapping analysis was then performed to ; predict the expected distribution of speed differences in 85th percentile speeds. This analysis also showed the 85th percentile ; speeds by the LiDAR gun and the Advance sensor were not significantly different for practical traffic engineering applications.
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Main Document Checksum:urn:sha256:fa8412d75e3f6b6dc41b82ef632c8885a6a2391c67241789dd6724349bb2fd66