基于改进SSD算法的限位器检测方法

Limiter Detection Method Based on Improved SSD Algorithm

自动泊车系统已经成为高级辅助驾驶系统(ADAS)中的一项重要功能,车辆在泊车过程中时常会出现泊车不到位、与相邻车位中的车辆发生剐蹭等事故。为提升自动泊车的精准性,文章提出了一种实时检测限位器的改进算法SSD-L,通过定位限位器的位置,对车辆的泊车位置进行修正。该方法对原先的SSD网络结构进行精简和改进,并使用卡尔曼滤波增加识别的稳定性。在实际泊车场景中的测试结果表明,SSD-L算法检测限位器的平均精度(mAP)较高,为95%。

Automatic parking system has become an important function of advanced driver assistance system(ADAS).In the process of parking,there are often accidents such as vehicle not parking in place and rubbing with vehicles in adjacent parking spaces.In order to improve the accuracy of automatic parking,an improved algorithm SSD-L for real-time detection of the limiter is proposed,which modifies the parking position of the vehicle by locating the position of the limiter.This method simplifies and improves the original SSD network structure,and uses Kalman filter to increase the stability of recognition.The test results in the actual parking scene show that SSD-L algorithm has a high average accuracy(mAP)of 95%for limiter.