Automated vehicles are a great promise for the future of transportation systems. However, safety assurance is still a major roadblock for the mass deployment of such vehicles. This is a great challenge especially for the perception systems that have to handle a diversity of environmental conditions and road users. Up to now, perception systems treat the complete environment and all traffic participants in the same way, although only a subset of all objects has an influence on vehicle safety. To close this gap, we present in this work a comprehensive definition of safety-relevant objects, and for the most critical area around the vehicle, the safety-relevant area. Using these definitions, we demonstrate that a common object detection system is not able to detect all safety-relevant objects, which will make new, safer approaches necessary in future.
Safe Perception: On Relevance of Objects for Vehicle Safety
19.09.2021
1546824 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Evaluating performance of autonomous vehicle perception system using relevance of objects
Europäisches Patentamt | 2024
|Using relevance of objects to assess performance of an autonomous vehicle perception system
Europäisches Patentamt | 2024
|USING RELEVANCE OF OBJECTS TO ASSESS PERFORMANCE OF AN AUTONOMOUS VEHICLE PERCEPTION SYSTEM
Europäisches Patentamt | 2022
|USING RELEVANCE OF OBJECTS TO ASSESS PERFORMANCE OF AN AUTONOMOUS VEHICLE PERCEPTION SYSTEM
Europäisches Patentamt | 2022
|PERCEPTION SYSTEM FOR ASSESSING RELEVANCE OF OBJECTS IN AN ENVIRONMENT OF AN AUTONOMOUS VEHICLE
Europäisches Patentamt | 2022
|