Study On Detection Of Ahead Vehicle Based On Millimeter-Wave Radar-vision

With the increasing quantity of automobile, the road traffic accident occurs so frequently that ithas become one of the major global economic and social issues. Rear-end collision in highway ismakes up the most part of traffic accidents. To avoid or reduce such traffic accidents, a system ofvehicle detection should be developed. When other vehicles appear in the front of the vehicle asobstacles, the system can warn the driver accurately in real time. And the system can get theinformation including distance speed and acceleration between the vehicle and the obstructivevehicle, which provide information to support the vehicle assistance system.Vehicles were detected by means of vision and millimeter-wave radar data fusion. Themillimeter-wave radar provides a first estimation of vehicle candidates with related lateral positionand distance information. The information is used to define a region of interest (ROI) on an imageobtained by the vision. An Adaboost object detection algorithm is utilized to scan the ROI andverify the detection of millimeter-wave radar.1.Determine the dangerous target based on the millimeter-wave radar. Firstly, objects wereranged according to the distance principle. Then the nearest object in the same lane was determinedas the first selection based on analysis of the measurement environment, and the target determinationwas then completed through a relevant target life cycle method.2.Vehicle detection based on the vision. It was trained using vehicle rear views andnegative-samples as training images. The image library was generated by graying method andnormalized method. Haar-like features were proposed by integral images. Combining Adaboostalgorithm the most important ones were selected.3.Data fusion method based on Millimeter-Wave Radar-vision. Data fusion method include twoaspects: data fusion method on space and in time. Build the data transmission of coordinate withdistance measurement model based on single motionless image. The distortion parameters wereacheived in the way of Zhengyou Zhang’s calibration principal. Data fusion in time was finished bythe multithread system.The software system and part of the algorithm which is used for vehicle detection and recognition have been developed based on Visual6.0. Pictures of IEEE International Workshop onPerformance Evaluation of Tracking and Surveillance (PETS) were provided to test the detectionsystem of ahead vhicle. The results of real image experiments have proved to be satisfactory.