多模型跟踪检测变道机动

K. Weiß, N. Kaempchen, A. Kirchner
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引用次数: 45

摘要

大众汽车研发了一种车辆周围感知系统,该系统通过使用单一型号的卡尔曼跟踪器,将不同的环境传感器数据集成到一个组合描述中。本文利用交互多模型算法(IMM)对跟踪系统进行扩展,以提高弯道跟踪的稳定性,并检测被观察目标车辆的变道情况。所应用的imm跟踪器使用专门的模型来处理部分受曲率估计影响的横向和纵向运动。该技术通过记录的测量数据序列进行了测试,显示出对目标动态行为的鲁棒跟踪和良好的拟合分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-model tracking for the detection of lane change maneuvers
Volkswagen research has developed a system for vehicle surround perception which integrates different sensor data of the environment into a combined description by using a single model Kalman tracker. This paper deals with the extension of the tracking system by means of an interacting multiple-model algorithm (IMM) to improve the tracking stability during curves and to detect lane changes of the observed target vehicle. The applied IMM-tracker uses specialized models for lateral and longitudinal motion that are partly affected by curvature estimation. The technique is tested with recorded sequences of measurement data and shows robust tracking and well-fitting classification of the dynamical behavior of the targets.
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