Use of probabilistic graphical methods for online map validation

Andrea Fabris, L. Parolini, Sebastian Schneider, A. Cenedese
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引用次数: 2

Abstract

In the world of autonomous driving, high resolution maps play a fundamental role. Such maps are highly accurate representations of the environment and are essential for all the algorithms of strategy and path planning operations. Unfortunately, it is not always possible to guarantee the total reliability of these maps and therefore it is necessary to design a procedure for their validation. In this paper we introduce a framework for validating map data at run-time based on probabilistic graphical models. Results from simulations show the capabilities of the proposed approach and highlight the need to find an appropriate balance between model accuracy and complexity.
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使用概率图形方法在线地图验证
在自动驾驶领域,高分辨率地图扮演着基础性的角色。这样的地图是对环境的高度精确的表示,对于所有策略和路径规划操作的算法都是必不可少的。不幸的是,不可能总是保证这些地图的完全可靠性,因此有必要设计一个程序来验证它们。本文介绍了一个基于概率图模型的运行时地图数据验证框架。仿真结果表明了所提出方法的能力,并强调了在模型精度和复杂性之间找到适当平衡的必要性。
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