Details

Autor(en) / Beteiligte

• Petrich, Dominik
• Azarfar, Darius
• Kuhnt, Florian
• Zollner, J. Marius

Titel

The Fingerprint of a Traffic Situation: A Semantic Relationship Tensor for Situation Description and Awareness

Ist Teil von

• 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018, p.429-435

Ort / Verlag

IEEE

Erscheinungsjahr

2018

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Many modern approaches for autonomous vehicles are still limited to a low-level data representation without considering complex relational information about their environment. This often leads to a generalization problem in complex situations where algorithms only perform well in tailored scenes. The general challenge lies in combining probabilistic information about partially observable traffic participants with a semantic description of the environment to reduce the complexity of a scene making it manageable. In this work, we present a novel approach for considering high-level information in traffic situations with respect to modeling a semantic representation of the vehicles' environment as well as uncertainties respecting their probabilities through relations between entities. The knowledge is described by first-order logic. Environmental information is stored in a multi-dimensional tensor which will be called Semantic Tensor. It allows to model complex scenes and functions as a very fast data structure. A novel similarity measure allows comparing any two Semantic Tensors to extract information about the spatiotemporal differences.