Traffic Incident Detection Based on mmWave Radar and Improvement Using Fusion with Camera

Abstract

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.

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications

“…Modern transportation systems rely increasingly on the availability and accuracy of traffic detector data to monitor operational traffic conditions and assess system performance. In practice, the traffic parameters are collected mainly by the magneto-electric induction detecting method [ 14 , 15 ], the floating vehicle method [ 16 , 17 ], the video image detecting method [ 18 ], and the radar detecting method. Compared with the other mentioned methods, the radar detection method has the advantages of convenient installation and low interference with traffic flow.…”

“…The fusion of radar and image has good complementary advantages for vehicle detection. In [ 17 ], an improved incident detection method based on radar–camera fusion is proposed. The detection accuracy is improved by the fusion system.…”

Traffic Video-Based Parking and Abandoned Object Event Detection

“…As a result, because the actual traffic is one of the features of the scene, the research does not rely on the backdrop but instead makes use of the basic 3D information of the target to recognize the target. It is valuable both in terms of theory and in terms of practice [5].…”