Evaluating Sequential Reasoning about Hidden Objects in Traffic

Truls Nyberg, José Manuel Gaspar Sánchez, Christian Pek, Jana Tumova, Martin Törngren
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Abstract

Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.
评估交通中隐藏对象的顺序推理
隐藏的交通参与者给自动驾驶汽车带来了巨大的挑战。以前的方法通常不使用以前的观察结果,导致过度保守的行为。在本文中,我们提出了对当前传感器视图之外的物体进行推理的工作的延续。我们的目标是在自主平台上演示我们最近提出的方法,并在使用真实传感器数据时评估其可靠性和实时性可行性。在不影响安全性的情况下,在真实平台上展示显著的驾驶性能提升,将是对自动驾驶领域的重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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