Traffic Peak Period Detection from an Image Processing View
Traffic peak period detection is very important for the guidance and control of traffic flow. Most common methods for traffic peak period detection are based on data analysis. They have achieved good performance. However, the detection processes are not intuitional enough. Besides that, the accuracy...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/2097932 |
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| _version_ | 1850219881474031616 |
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| author | Jianli Xiao Hang Li Xiang Wang Shangcao Yuan |
| author_facet | Jianli Xiao Hang Li Xiang Wang Shangcao Yuan |
| author_sort | Jianli Xiao |
| collection | DOAJ |
| description | Traffic peak period detection is very important for the guidance and control of traffic flow. Most common methods for traffic peak period detection are based on data analysis. They have achieved good performance. However, the detection processes are not intuitional enough. Besides that, the accuracy of these methods needs to be improved further. From an image processing view, we introduce a concept in corner detection, sharpness, to detect the traffic peak periods in this paper. The proposed method takes the traffic peak period detection problem as a salient point detection problem and uses the image processing strategies to solve this problem. Firstly, it generates a speed curve image with the speed data. With this image, the method for detection of salient points is adopted to obtain the peak point candidates. If one candidate has the lowest speed value, this candidate is the peak point. Finally, the peak period is gotten by moving forward and backward the corresponding time of the peak point with a time interval. Experimental results show that the proposed method has achieved higher accuracy. More importantly, as the proposed method solves the traffic peak period detection problem from an image processing view, it has more intuition. |
| format | Article |
| id | doaj-art-762276d7795b41bf95bc161907deffa6 |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-762276d7795b41bf95bc161907deffa62025-08-20T02:07:15ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/20979322097932Traffic Peak Period Detection from an Image Processing ViewJianli Xiao0Hang Li1Xiang Wang2Shangcao Yuan3Shanghai Key Lab of Modern Optical System and Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, No. 516 JunGong Road, Shanghai 200093, ChinaShanghai Key Lab of Modern Optical System and Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, No. 516 JunGong Road, Shanghai 200093, ChinaShanghai Key Lab of Modern Optical System and Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, No. 516 JunGong Road, Shanghai 200093, ChinaShanghai Key Lab of Modern Optical System and Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, No. 516 JunGong Road, Shanghai 200093, ChinaTraffic peak period detection is very important for the guidance and control of traffic flow. Most common methods for traffic peak period detection are based on data analysis. They have achieved good performance. However, the detection processes are not intuitional enough. Besides that, the accuracy of these methods needs to be improved further. From an image processing view, we introduce a concept in corner detection, sharpness, to detect the traffic peak periods in this paper. The proposed method takes the traffic peak period detection problem as a salient point detection problem and uses the image processing strategies to solve this problem. Firstly, it generates a speed curve image with the speed data. With this image, the method for detection of salient points is adopted to obtain the peak point candidates. If one candidate has the lowest speed value, this candidate is the peak point. Finally, the peak period is gotten by moving forward and backward the corresponding time of the peak point with a time interval. Experimental results show that the proposed method has achieved higher accuracy. More importantly, as the proposed method solves the traffic peak period detection problem from an image processing view, it has more intuition.http://dx.doi.org/10.1155/2018/2097932 |
| spellingShingle | Jianli Xiao Hang Li Xiang Wang Shangcao Yuan Traffic Peak Period Detection from an Image Processing View Journal of Advanced Transportation |
| title | Traffic Peak Period Detection from an Image Processing View |
| title_full | Traffic Peak Period Detection from an Image Processing View |
| title_fullStr | Traffic Peak Period Detection from an Image Processing View |
| title_full_unstemmed | Traffic Peak Period Detection from an Image Processing View |
| title_short | Traffic Peak Period Detection from an Image Processing View |
| title_sort | traffic peak period detection from an image processing view |
| url | http://dx.doi.org/10.1155/2018/2097932 |
| work_keys_str_mv | AT jianlixiao trafficpeakperioddetectionfromanimageprocessingview AT hangli trafficpeakperioddetectionfromanimageprocessingview AT xiangwang trafficpeakperioddetectionfromanimageprocessingview AT shangcaoyuan trafficpeakperioddetectionfromanimageprocessingview |