| Autor: |
Zhimin Tao, Yanbing Li, Pengcheng Wang, Lianying Ji |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Journal of Advanced Transportation, Vol 2022 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2042-3195 |
| DOI: |
10.1155/2022/2286147 |
| Popis: |
Improving traffic efficiency and safety is the goal of all countries due to the increasingly congested road environment worldwide. The progress of intelligence has promoted the development of the transportation industry. As the first step to intelligence, perception technology is an important part to realize intelligent transportation. Accurate and efficient traffic management systems, such as the automatic control of traffic lights at urban intersections or highway emergency disposal, need the support of advanced environmental sensing technology. In the application of traffic perception, millimeter wave radar and camera are two important sensors. Radar has been widely used in traffic incident perception due to its all-weather working capability; however, there are problems such as inability to detect stationary targets and poor target classification performance. Camera has the advantages of accurate target angle information measurement and rich details, but there are problems of inaccurate ranging and speed measurement and performance degradation in harsh weather conditions. Considering the complementary characteristics of the two sensors in information, an improved incident detection method based on radar-camera fusion is proposed. This method combines the advantages of millimeter wave radar and camera and improves the robustness of the traffic incident detection system. The detection performance is verified in the real experiment. The results show that the detection accuracy of the proposed fusion system is better than that of a single millimeter wave radar in all scenarios, and the accuracy is improved by more than 50% in some cases. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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