Connected Vehicle Perception Monitoring: A Runtime Verification Approach for Enhanced Autonomous Driving Safety

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Kurzfassung

Modern autonomous vehicles rely heavily on complex sensor systems for perception tasks, including Advanced Driver Assistance Systems and Autonomous Driving Systems. Accurate sensor perception is essential to ensure the safety of these systems, especially as the level of automation increases. External sensors from the infrastructure or other vehicles can provide useful information to verify the trustworthiness of on-vehicle sensors using V2X communication. This paper presents a novel concept of runtime monitoring to verify the performance of ADS perception systems, taking advantage of the design diversity of connected vehicles and infrastructure based perception sensors in Intelligent Transportation Systems. The proposed approach uses standardised V2X services, such as Collective Perception Service and Location Service from connected participants to estimate a reliable common environment model (CEM) of the driving situation. The established CEM can be used to evaluate the quality of perception of individual road participants during operation, allowing detection and mitigation of system malfunctions of a connected vehicle perception system and enhancing road safety in connected environments. We also discuss open design questions with respect to the perception runtime monitor concept.

Verfügbare Versionen dieses Eintrags

• Connected Vehicle Perception Monitoring: A Runtime Verification Approach for Enhanced Autonomous Driving Safety. (deposited 15 Mai 2024 16:11) [Gegenwärtig angezeigt]