Masaya Kikuzawa
ABSTRACT
Recently, traffic congestions caused by increase of vehicle possession and complicatedness of traffic system have induced several serious social problems. In order to solve these problems, a lot of attempts have been carried out in many areas including new type of traffic signal system employing fuzzy control or neural network system. In addition to that system, a visualized miniature traffic simulation system based on real road system has been developed to examine the performance of the new traffic signal system and its effectiveness has been proved in several problems, which cannot sufficiently model that is able to reproduce the real traffic behaviors. In this study, a traffic flow measurement system has been developed to extract traffic flow data by analyzing images from the fixed point cameras set up near intersections. The measurement system has been developed by optical flow and R-CNN, and its performance was evaluated based on the recognition rate of the number of cars passing the intersection and the recognition rate of matching for same vehicle and the accuracy of the means speed estimated by the difference of passage time at two intersections. The result showed that the new system has higher rate of matching for same vehicle than previous study.
- M. Jeong, and M. Kikuzawa, "Development of Traffic Flow Measurement System Using Fixed Point Cameras," Dynamics and Design Conference 2018, Transactions of the Japan Society of Mechanical Engineer, Paper No. 628, August 2018.Google Scholar
- M. Jeong, and M. Hagiwara, "Development of Traffic Flow Measurement System Using Fixed Point Cameras", vol. 16. Annual meeting, National Institute of Technology, Numazu College Advanced Course, pp. 71--74, January 2018.Google Scholar
- E. Ohta, "Deeplearning for Image Processing~Recognizing and detecting objects by CNN and R-CNN~,Unpublished"Google Scholar
- D. Patel,S.Upadhyay,"Optical Flow Measurement using Lucas kanade Method", International Journal of Computer Applications, vol. 61, pp. 6--10, January 2013Google ScholarCross Ref
- R. Girshick, J. Donahue, T. Darrell and J. Malik, "Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation", CVPR '14 Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 580--587, June, 2018 Google ScholarDigital Library
Index Terms
- Development of Traffic Flow Measurement System Using Fixed Point Cameras
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