摘要
为了增强自适应巡航系统的性能,本文提出一种基于语义点云的巡航系统移动目标轨迹识别方法。该方法的核心竞争力在于其实时且高精度的移动目标轨迹识别能力,针对复杂道路环境,将点云曲率信息融入特征点搜索与匹配过程中,并结合相似度函数完成点云配准,在此基础上得到移动目标轨迹。经过一系列实验测试,验证了本文方法的可靠性与优越性,可为自适应巡航系统广泛应用提供一定的技术支撑,有效提升系统识别不同移动模型下目标轨迹的能力。
To enhance the performance of adaptive cruise control systems,this paper proposes a moving target trajectory recognition approach for cruise systems based on semantic point clouds.The core competitiveness of this method lies in its real-time and high-accuracy capability for identifying moving target trajectories.Addressing the challenges of complex road environments,curvature information from the point clouds is integrated into the feature point searching and matching process,and point cloud registration is accomplished in conjunction with a similarity function.Based on this,the moving target trajectories are derived.A series of experimental tests have validated the reliability and superiority of the proposed method,this approach can provide technical support for the widespread adoption of adaptive cruise control systems,effectively enhancing their capability to identify target trajectories under different moving models.
作者
吴佐成
WU Zuocheng(Fujian Satellite Data Development Co.,Ltd.,Fuzhou 350001,China)
出处
《测绘与空间地理信息》
2025年第7期128-131,142,共5页
Geomatics & Spatial Information Technology
关键词
移动目标
轨迹识别
自适应巡航系统
点云滤波
语义分割
moving targets
trajectory recognition
adaptive cruise control systems
point cloud filtering
semantic segmentation
