基于多维特征融合的服务区小客车载客系数检测方法OA

In view of the frequent interaction between pedestrians and vehicles,and the lack of consistency in cross category tracking in expressway service areas,which leads to difficulties in passenger coefficient detection,low detection accuracy and poor robustness,a passenger coefficient of passenger cars detection method based on multi-dimensional feature fusion is proposed to improve the accuracy of service area operation data.Firstly,YOLOv10x and ByteTrack are used as detection and tracking modules to build a detection system incorporating multi-dimensional features.Secondly,the Kalman filter method is used to predict the target trajectory and establish the target motion prior,and the classification feature extraction method is introduced to extract the appearance semantic features of vehicles and pedestrians respectively;An adaptive weighted association strategy based on detection confidence is designed,and multi-dimensional feature fusion is carried out.The Hungarian Algorithm is utilized to realize target re-identification(ReID)and matching.Finally,the passenger coefficient is detected based on the monitoring video in the service area,and the algorithm is compared and analyzed by indicators such as tracking accuracy,tracking precision,ID switches,and frame rate.The experimental results show that:the detection method based on multi-dimensional feature fusion can accurately count the passenger coefficient.Compared with the traditional ByteTrack algorithm that relies solely on IOU matching for object tracking,its tracking accuracy and tracking precision are improved by 0.99%and 16.09%,respectively,and the number of ID switches is reduced by 151,representing a 18.33%reduction.This method can significantly improve accuracy and robustness in complex traffic scenes while ensuring inference speed,and can make up for the lack of passenger coefficient statistics in the service area,which can provide a theoretical basis for improving the operation management and service efficiency of the service area,and provide a reference for calculating the actual loading rate on the expressway.