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  4. Safety Implications of Runtime Adaptation to Changing Operating Conditions
 
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2022
Conference Paper
Title

Safety Implications of Runtime Adaptation to Changing Operating Conditions

Abstract
With further advancements of autonomous driving, also larger application scenarios will be addressed, so-called Operational Design Domains (ODDs). Autonomous vehicles will likely experience varying operating conditions in such broader ODDs. The implications of changing operating conditions on safety and required adaptation is, however, an open challenge. In our work, we exemplary investigate a vehicle following scenario passing through altering operating conditions and Responsibility Sensitive Safety (RSS) as formal model to define appropriate longitudinal following distances. We provide a deeper analysis of the influence of switching the safety model parameter values to adapt to new operating conditions. As our findings show that hard switches of operating conditions can lead to critical situations, we propose an approach for continuously adapting safety model parameters allowing for a safe and more comfortable transition. In our evaluation, we utilize driving simulations to compare the hard switching of parameters with our proposal of gradual adaptation. Our results highlight the implications of changing operating conditions on the driving safety. Moreover, we provide a solution to adapt the safety model parameters of an autonomous vehicle in such a way that safety model violations during transition can be avoided.
Author(s)
Salvi, Aniket  
Fraunhofer-Institut für Kognitive Systeme IKS  
Weiß, Gereon  
Fraunhofer-Institut für Kognitive Systeme IKS  
Trapp, Mario  
Fraunhofer-Institut für Kognitive Systeme IKS  
Oboril, Fabian
Intel Deutschland, Neubiberg  
Buerkle, Cornelius
Intel Deutschland, Neubiberg  
Mainwork
IEEE 25th International Conference on Intelligent Transportation Systems, ITSC 2022  
Project(s)
IKS-Aufbauprojekt  
Entwicklung einer risikosensitiven Gesamtsystemarchitektur und echtzeitfähiger Methoden zur Absicherung von Automatisierten Fahrzeugen  
Safe Automated Vehicles
Funder
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie
Bundesministerium für Wirtschaft und Klimaschutz -BMWK-
Intel Collaborative Research Institute
Conference
International Conference on Intelligent Transportation Systems 2022  
Open Access
DOI
10.1109/ITSC55140.2022.9922192
10.24406/h-428428
File(s)
Salvi_SafetyImplicationsOfRuntimeAdaptationToChangingOperatingConditions_2210_ITSC (002).pdf (336.42 KB)
Rights
Under Copyright
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie  
Keyword(s)
  • autonomous driving

  • autonomous vehicle

  • Operational Design Domain

  • OOD

  • safety

  • responsibility sensitive safety

  • RSS

  • safety model

  • runtime adaptation

  • automated vehicle

  • AV

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