Anomaly Detection in Radar Data Using PointNets
- Thomas Griebel, Dominik Authaler, Markus Horn, M. Henning, M. Buchholz, K. Dietmayer
- Computer ScienceInternational Conference on Intelligent…
- 19 September 2021
This work presents an approach based on PointNets to detect anomalous radar targets, and developed a novel grouping variant which contributes to a multi-form grouping module in urban scenarios.
Automation of the UNICARagil Vehicles
- M. Buchholz, Fabian Gies, Norbert Siepenkötter
- Computer Science
- 5 October 2020
Situation-Aware Environment Perception Using a Multi-Layer Attention Map
- M. Henning, Johannes Müller, Fabian Gies, M. Buchholz, K. Dietmayer
- Computer ScienceIEEE Transactions on Intelligent Vehicles
- 2 December 2021
This work introduces a concept for situation-aware environment perception to control the resource allocation towards processing relevant areas within the data as well as towards employing only a subset of functional modules for environment perception, if sufficient for the current driving task.
A mobile measurement system for urban immission-monitoring using satellite navigation
- J. Wöllenstein, S. Rademacher, A. Eberhardt, M. Henning, W. Schönewolf
- Environmental Science
- 2010
Situation-Aware Environment Perception for Decentralized Automation Architectures
- M. Henning, M. Buchholz, K. Dietmayer
- Computer ScienceIEEE Intelligent Vehicles Symposium (IV)
- 5 June 2022
This work extends the applicability range of the recently introduced concept for situation-aware environment perception to the decentralized automation architecture of the UNICARagil project and shows the need to consider scalability in data processing in the design of software modules as well as in theDesign of functional systems if the benefits of situation-awareness shall be leveraged optimally.
Identification of Threat Regions From a Dynamic Occupancy Grid Map for Situation-Aware Environment Perception
- M. Henning, Jan Strohbeck, M. Buchholz, K. Dietmayer
- Computer ScienceIEEE 25th International Conference on Intelligent…
- 5 July 2022
This work presents a lightweight identification of safety-relevant regions that relies solely on online information and shows that this approach enables safe vehicle operation in critical scenarios, while retaining the benefits of non-uniformly distributed resources within the environment perception.