A computer-implemented method and system for behavioral planning of traffic scene participants is presented. To this end, a mesh-based scene representation (30) is generated on the basis of the aggregated scene-specific information and is divided into a plurality of blocks (35), each representing a sub-region of the traffic scene. According to the invention, the scene-specific information is distributed over at least two semantic levels of the scene representation (30). The distribution is maintained when divided into a plurality of chunks (35) to form at least one type of sub-chunks (351, 352, 353, 354) based on these chunks (35) and semantic levels. Then, the mesh-based scene representation (30) is mapped to potential features based on these tiles (35) or sub-tiles (351, 352, 353, 354), where semantic relationships between at least one type of tiles (35) or sub-tiles (351, 352, 353, 354) are taken into account. Potential features generated in this way are used as inputs for at least one downstream DL (deep learning) module to predict the development of a traffic scene and/or for behavioral planning.
提出了一种用于交通场景参与者的行为规划的计算机实现的方法和系统。为此,基于聚合的场景特定信息生成基于网格的场景表示(30),并将其划分为多个分块(35),这些分块分别表示该交通场景的子区域。根据本发明,场景特定信息被分布到场景表示(30)的至少两个语义层面上。当划分为多个分块(35)时维持所述分布,以基于这些分块(35)和语义层面形成至少一种类型的子分块(351、352、353、354)。然后,基于这些分块(35)或子分块(351、352、353、354)将所述基于网格的场景表示(30)映射到潜在特征,其中考虑至少一种类型的分块(35)或子分块(351、352、353、354)之间的语义关系。以这种方式生成的潜在特征被用作针对至少一个下游的DL(深度学习)模块的输入,以预测交通场景的发展和/或用于行为规划。
Computer-implemented method and system for behavioral planning of traffic scene participants
用于交通场景参与者的行为规划的计算机实现的方法和系统
2024-12-03
Patent
Electronic Resource
Chinese
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