Ontology based Scene Creation for the Development of Automated Vehicles
By Gerrit Bagschik, Till Menzel, Markus Maurer. 2018 IEEE Intelligent Vehicles Symposium (IV), 2017
309 citations recorded by the source corpus.
The introduction of automated vehicles without permanent human supervision demands a functional system description, including functional system boundaries and a comprehensive safety analysis. These inputs to the technical development can be identified and analyzed by a scenario-based approach. Furthermore, to establish an economical test and release process, a large number of scenarios must be identified to obtain meaningful test results. Experts are doing well to identify scenarios that are difficult to handle or unlikely to happen. However, experts are unlikely to identify all scenarios possible based on the knowledge they have on hand. Expert knowledge modeled for computer aided processing may help for the purpose of providing a wide range of scenarios. This contribution reviews ontologies as knowledge-based systems in the field of automated vehicles, and proposes a generation of traffic scenes in natural language as a basis for a scenario creation.
View Paper: https://www.semanticscholar.org/paper/fd41752ccdbee19ebc5a8a6a3d62144472ff14a4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Xue Yang
- Wen Qian
- Julian Bock
- Silong Peng
- Yue Guo
- Chi Yan
- Robert Krajewski
- Stefan Riedmaier
Citations in the corpus
- Learning Modulated Loss for Rotated Object Detection (2019, background): “Object detection has been extensively applied in face detection [6, 7], automatic driving [8], optical text detection [9], and other fields.”
- The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems (2018, methodology): “5-Layer model for the description of scenarios as in [5].”
- Survey on Scenario-Based Safety Assessment of Automated Vehicles (2020, methodology): “For this purpose, a five-layer model is presented in [21] to structure the param-”