使用嵌入式软核处理器的高级驾驶员辅助系统的数据关联技术

Jehangir Khan, C. Tatkeu, P. Deloof, S. Niar
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引用次数: 1

摘要

用于汽车应用的高级驾驶辅助系统(ADAS)用于减少道路交通事故的数量。多目标跟踪(MTT)是现代ADAS中最有效的技术之一。数据关联是MTT的一个重要组成部分,它可以被建模为经典的分配问题。我们使用NiosII软核处理器在Altera的StratixII FPGA中实现了两种算法,即Munkres(或Hungarian)算法和Auction算法。分析了两种算法的资源需求和执行速度。我们描述了在数据关联问题的上下文中使用这两种算法中的一种或另一种最合适的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data association techniques for advanced driver assistance systems using embedded soft-core processors
Advanced Driver Assistance Systems (ADAS) for automotive applications are used to reduce the number of road accidents. Multiple Target Tracking (MTT) is one of the most efficient techniques used in modern ADAS's. Data Association is a vital part of MTT which can be modeled as the classic Assignment Problem. We implement two algorithms namely, the Munkres (or Hungarian) algorithm and the Auction algorithm in Altera's StratixII FPGA using the NiosII soft-core processor. We analyze the resource requirements and the execution speed of the two algorithms. We describe the circumstances where the use of one or the other of these two algorithms is most suitable in the context of the data association problem.
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