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Multiple-model tracking for the detection of lane change maneuvers

机译:用于跟踪车道变更动作的多模型跟踪

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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.
机译:大众汽车研究公司开发了一种用于车辆周围感知的系统,该系统通过使用单个模型卡尔曼跟踪器将环境的不同传感器数据整合到组合描述中。本文通过交互式多模型算法(IMM)处理跟踪系统的扩展问题,以提高弯道期间的跟踪稳定性并检测观察到的目标车辆的车道变化。所应用的IMM跟踪器对横向和纵向运动使用专门的模型,这些模型部分受曲率估计的影响。该技术已通过记录的测量数据序列进行了测试,并显示了目标动态行为的可靠跟踪和良好拟合的分类。

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