智能系统学报2025，Vol.20Issue(6)：1328-1338,11.DOI:10.11992/tis.202503034
基于恒定转弯率和加速度模型的点云多目标跟踪算法
Point cloud multitarget tracking algorithm based on the constant turn rate and acceleration model
摘要
Abstract
To address the suboptimal performance of simple motion models in the context of multitarget tracking within intricate driving environments,this paper proposes a point cloud-based multitarget tracking method that utilizes the con-stant turn rate and acceleration(CTRA)model.By incorporating angular velocity into the motion model to describe ob-ject trajectories,the method improves tracking accuracy during turning maneuvers.Furthermore,the velocity informa-tion provided by the detection algorithm is leveraged to correct object speeds during trajectory updates,enhancing ro-bustness under sudden velocity changes.Moreover,a confidence-based two-stage matching strategy is employed to mit-igate the influence of low-confidence detections on tracking results.The proposed 3D object detection and tracking al-gorithm is evaluated on the nuScenes validation set,and ablation studies are conducted to verify the effectiveness of each module.Experimental results demonstrate that the CTRA-based point cloud multitarget tracking algorithm exhibits superior performance in terms of tracking accuracy,significantly enhances performance in turning and abrupt velocity change scenarios,and substantially reduces identity switches during tracking when compared to simple motion models.关键词
点云/多目标跟踪/深度学习/自动驾驶/置信度二阶段匹配/非线性运动/数据关联/匈牙利算法Key words
point cloud/multitarget tracking/deep learning/autonomous driving/confidence-based two-stage matching/nonlinear dynamics/data association/Hungarian algorithm分类
信息技术与安全科学引用本文复制引用
LU Jun,WANG Xudong,JI Guangyu,LI Yang..基于恒定转弯率和加速度模型的点云多目标跟踪算法[J].智能系统学报,2025,20(6):1328-1338,11.基金项目
黑龙江省自然科学基金项目(F201123). （F201123）
