Abstract: An improved real-time target-vehicles detection algorithm SSD-P was developed focusing on overlapping small target-vehicles in actual traffic scenes to improve the detection accuracy using an advanced driver assistance system (ADAS). This algorithm was based on two methods: 1) a resolution reconstruction method of shallow feature image was proposed by increasing the number of small target feature extraction; 2) a quadratic determination method with embedded feature vector in non-maximal suppression to overcome the problems such as low precision and weak ability of overlapping target detection in a single shot multi-box detector (SSD) algorithm. Experiments were carried out in PASCAL VOC2012 data set, virtual traffic scene and real traffic scene. The results show that the mean accuracy precision (mAP) for target vehicle detection is 92.4% by using SSD-P algorithm, this is 4.8% higher than that by using the original SSD algorithm. Therefore, the SSD-P algorithm can improve the accuracy of ADAS.  

Key words: advanced driver assistance system, ADAS, real-time vehicle detections, single shot multi-box detector (SSD) algorithm, small targets, overlapping objectives, vehicle detections