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2023
Paper (Preprint, Research Paper, Review Paper, White Paper, etc.)
Title

Uncertainty-aware RSS

Title Supplement
Position Paper published on HAL science ouverte
Abstract
In this preliminary work, the authors present a potential solution on the issue of real time parameter estimation within a safety critical application. When computing the frontal safety distance, each vehicles type requires, in principle, a different safety distances depending on its capability to brake at a greater or lower rate. In order to account for different braking capabilities, an object detection and recognition algorithm must be employed, and thus, some classification uncertainty is introduced in the system. We propose to employ such a solution, in order to maximise the utility of the system by accounting for different vehicle types, while considering the uncertainty, in order to preserve safety.
Author(s)
Carella, Francesco
Fraunhofer-Institut für Kognitive Systeme IKS  
Oleinichenko, Oleg  
Fraunhofer-Institut für Kognitive Systeme IKS  
Schleiß, Philipp  
Fraunhofer-Institut für Kognitive Systeme IKS  
Project(s)
IKS-Aufbauprojekt  
Funder
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie  
Conference
International Conference on Computer Safety, Reliability and Security 2023  
Link
Link
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie  
Keyword(s)
  • real-time parameter estimation

  • safety critical

  • safety critical application

  • safety distance

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