The purpose of this study was to compare cycle flows and speeds from two different cycle measurement equipment. The result has also been compared with the processed video data and manual counts. The measuring equipment are Viscando’s equipment OTUS3D and VTI´s TA-89. OTUS3D is a camera with 3D functionality, and it detects tracks and classifies these into different road user categories. TA-89 (where TA stands for Traffic Analyzer) is developed by VTI and is adapted for detecting both bicycles and motor vehicles. We also used a video camera from the OTUS3D system, to enable a manual calculation. The test site for the study is a pedestrian and bicycle path that crosses a ridge in Vallaskogen in Linköping. The area is located between the district of East Valla and campus. It is a fairly steep slope where the direction towards the campus is uphill and the direction to the East Valla / city center is downhill. Five days that did not include losses of flow were selected for the analyzes. The selected periods were 3 to 4 September (Saturday and Sunday) and 6 to 8 September (Tuesday to Thursday). In addition to this, we chose an hour with high flow and an hour with low flow where video processing was conducted. Furthermore, we used an hour and 50 minutes of manual counting. During the five selected days, OTUS3D registered 8 266 cyclists and TA-89 registered 9 446 cyclists. Towards the city center, the number of registered cyclists were 4 567 in TA-89 and 3 309 in OTUS3D, which means a difference of 1 258 registrations. In the direction of the university area, the registered cycle flow was considerably more even, only a difference of 78 cyclists, with OTUS3D having the higher number of registrations. The measured average speed was 25.1 kilometers per hour and 25.5 kilometers per hour towards the city center of OTUS3D and TA-89, respectively. In the direction of the campus the average speed was 14.1 kilometers per hour in OTUS3D and 13.0 km/h in TA-89. Regarding the hour with high and low flow, both OTUS3D and TA-89 gave similar results. When comparing these measuring systems to the video processing results in the direction of the city center during high flow, they both underestimated the speed by just over 1.5 kilometers per hour. In the direction of the campus during the hour with high cycle flow OTUS3D and video had the same average speed while TA-89 underestimated the speed by 1.1 kilometers per hour. In the direction of the city center during low flow, there was no large difference in average speed between TA-89 and the measured speed of video, while OTUS3D registered 0.5 kilometers per hour higher average speed compared to video. In the direction of the campus during low cycle flow OTUS3D had 0.9 kilometers per hour higher average speed than the video, while there is no major difference between the TA-89 and video. During the selected period with manual counting based on a video 578 cyclists passed in both directions. OTUS3D detected 545 cyclists and TA-89 detected 441 cyclists. This gives a detection rate of 94.3 percent for OTUS3D and 95.3 percent for TA-89. There is no produced average speed from the video during this period. Our conclusion from the study is that there is a difference in the cycle flow detection between the cycle measurement equipment (OTUS3D and TA-89). The difference, however, largely depends on something that seems to have happened with the OTUS3D-registration at the end of the period, to which we cannot find any explanations. There is, however, no significant difference in the measured average speed between the equipment. (Author/publisher)
Abstract