摘要
针对自卸车外形尺寸大导致车辆右转弯时存在较大视野盲区的问题,提出一种自卸车右转盲区风险目标动态检测算法,该算法利用YOLOv8模型的C2f模块和损失计算模块,提高了模型的检测精确率。同时,在盲区中预设4条位置阈值线,增加盲区风险预警模块,建立了自卸车右转盲区辅助驾驶系统。结果表明:所提出的风险目标动态检测算法能够识别小型乘用车、载货汽车、公交车、行人和电动自行车等多种类型的目标,且所有类别目标的50%交并比阈值下的平均精度均值(mAP50)为0.87;自卸车右转盲区辅助驾驶系统能够根据图像中风险目标框的位置进行不同程度的预警。
To address the issue of extensive blind spots during right turns due to the oversized nature of dump trucks,this paper proposes a dynamic detection algorithm for risk targets in the right-turn blind spots of dump trucks.The algorithm improves the YOLOv8 model by enhancing the C2f module and lossing calculation module to refine the model’s detection accuracy.Additionally,four position threshold lines are preset in the blind spots,the risk warning module of the blind spots of the dump truck is added,and the auxiliary driving system of the blind spots of the dump truck is established.The results indicate that the proposed dynamic detection algorithm can recognize various types of targets,including cars,trucks,buses,pedestrians and electric bicycles,with a mean Average Precision(mAP50)of 0.87 at a 50%intersection over union threshold for all categories of targets.The right-turn blind spots assisted driving system of the dump truck can make different degrees of early warning according to the position of the risk target box in the image.
作者
贺鹏麟
陈志芳
王畅
He Penglin;Chen Zhifang;Wang Chang(Shenzhen Smart Chelian Technology Co.,Ltd.,Shenzhen 518100;Zhejiang Haikang Technology Co.,Ltd.,Hangzhou 310000;Chang’an University,Xi’an 710064)
出处
《汽车工程师》
2024年第8期36-41,共6页
Automotive Engineer
