Dynamic-preserving qualitative motion description for intelligent vehicles

A. Miene, Andreas D. Lattner, Ubbo Visser, O. Herzog
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引用次数: 16

Abstract

Planning, acting, and recognizing intentions of participants in traffic situations requires the processing of complex spatio-temporal situations. If spatio-temporal information was represented quantitatively it would result in a huge amount of data. We claim that an abstraction to a qualitative description leads to more stable representations as similar situations at the quantitative level are mapped to one qualitative representation. Our approach is evaluated by emulating traffic situations with settings in the Robocup small-sized league.
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智能车辆的保动态定性运动描述
交通情景中参与者的规划、行动和意图识别需要处理复杂的时空情景。如果对时空信息进行量化表示,将会产生大量的数据。我们声称,定性描述的抽象导致更稳定的表征,因为在定量水平上的类似情况被映射到一个定性表征。我们的方法是通过模拟Robocup小型联赛中的交通状况来评估的。
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