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Stationary environment models for Advanced Driver Assistance Systems

机译:高级驾驶员辅助系统的固定环境模型

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The vision of a fully self-driving autonomous car is year by year closer to be achieved. The crucial part of this vision is the perception which is carried by complex algorithms processing signals coming from a set of different sensors. A selfdriving car has to know locations of stationary obstacles in its surrounding. This paper is an overview of existing models used to describe the stationary environment. Grid models like 1D, 2D or 3D discrete maps, primitive structures and free space boundary contours are described with some illustrative examples. Models are compared from the point of view of description completeness as well as applications. Estimates of memory consumption are also given.
机译:全自动无人驾驶自动驾驶汽车的愿景逐年逼近。此愿景的关键部分是感知,它是由复杂算法处理的信号,这些算法处理来自一组不同传感器的信号。无人驾驶汽车必须知道其周围固定障碍物的位置。本文概述了用于描述静止环境的现有模型。用一些说明性示例描述了诸如1D,2D或3D离散图,原始结构和自由空间边界轮廓之类的网格模型。从描述完整性和应用程序的角度比较模型。还给出了内存消耗的估计值。

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