Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones
Great changes have taken place in automation and machine vision technology in recent years. Meanwhile, the demands for driving safety, efficiency, and intelligence have also increased significantly. More and more attention has been paid to the research on advanced driver-assistance system (ADAS) as...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8883639 |
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| _version_ | 1832550500632887296 |
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| author | Liyong Wang Peng Sun Min Xie Shaobo Ma Boxiong Li Yuchen Shi Qinghua Su |
| author_facet | Liyong Wang Peng Sun Min Xie Shaobo Ma Boxiong Li Yuchen Shi Qinghua Su |
| author_sort | Liyong Wang |
| collection | DOAJ |
| description | Great changes have taken place in automation and machine vision technology in recent years. Meanwhile, the demands for driving safety, efficiency, and intelligence have also increased significantly. More and more attention has been paid to the research on advanced driver-assistance system (ADAS) as one of the most important functions in intelligent transportation. Compared with traditional transportation, ADAS is superior in ensuring passenger safety, optimizing path planning, and improving driving control, especially in an autopilot mode. However, level 3 and above of the autopilot are still unavailable due to the complexity of traffic situations, for example, detection of a temporary road created by traffic cones. In this paper, an analysis of traffic-cone detection is conducted to assist with path planning under special traffic conditions. A special machine vision system with two monochrome cameras and two color cameras was used to recognize the color and position of the traffic cones. The result indicates that this novel method could recognize the red, blue, and yellow traffic cones with 85%, 100%, and 100% success rate, respectively, while maintaining 90% accuracy in traffic-cone distance sensing. Additionally, a successful autopilot road experiment was conducted, proving that combining color and depth information for recognition of temporary road conditions is a promising development for intelligent transportation of the future. |
| format | Article |
| id | doaj-art-88a4da96caa744d99f5fce7fc255f1d5 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-88a4da96caa744d99f5fce7fc255f1d52025-02-03T06:06:32ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88836398883639Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic ConesLiyong Wang0Peng Sun1Min Xie2Shaobo Ma3Boxiong Li4Yuchen Shi5Qinghua Su6Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaKey Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaComputer School, Beijing Information Science and Technology University, Haidian District, Beijing 100101, ChinaKey Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaKey Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaKey Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaKey Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science & Technology University, Haidian District, Beijing 100192, ChinaGreat changes have taken place in automation and machine vision technology in recent years. Meanwhile, the demands for driving safety, efficiency, and intelligence have also increased significantly. More and more attention has been paid to the research on advanced driver-assistance system (ADAS) as one of the most important functions in intelligent transportation. Compared with traditional transportation, ADAS is superior in ensuring passenger safety, optimizing path planning, and improving driving control, especially in an autopilot mode. However, level 3 and above of the autopilot are still unavailable due to the complexity of traffic situations, for example, detection of a temporary road created by traffic cones. In this paper, an analysis of traffic-cone detection is conducted to assist with path planning under special traffic conditions. A special machine vision system with two monochrome cameras and two color cameras was used to recognize the color and position of the traffic cones. The result indicates that this novel method could recognize the red, blue, and yellow traffic cones with 85%, 100%, and 100% success rate, respectively, while maintaining 90% accuracy in traffic-cone distance sensing. Additionally, a successful autopilot road experiment was conducted, proving that combining color and depth information for recognition of temporary road conditions is a promising development for intelligent transportation of the future.http://dx.doi.org/10.1155/2020/8883639 |
| spellingShingle | Liyong Wang Peng Sun Min Xie Shaobo Ma Boxiong Li Yuchen Shi Qinghua Su Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones Advances in Civil Engineering |
| title | Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones |
| title_full | Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones |
| title_fullStr | Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones |
| title_full_unstemmed | Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones |
| title_short | Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones |
| title_sort | advanced driver assistance system adas for intelligent transportation based on the recognition of traffic cones |
| url | http://dx.doi.org/10.1155/2020/8883639 |
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