Authors:
Alexander Stocker
;
Tahir Emre Kalayci
;
Michael Spitzer
and
Gerald Musser
Affiliation:
Virtual Vehicle Research GmbH, Inffeldgasse 21a, 8010 Graz, Austria
Keyword(s):
Software-Defined Vehicles, Connected Vehicles, Driver Warning, Driver Monitoring, Data Sharing, Data Ecosystems.
Abstract:
Web technologies, Internet of Things (IoT) frameworks, and modern communication standards are increasingly transforming the automotive sector, giving rise to software-defined vehicles. These vehicles operate as connected entities within a broader digital ecosystem, enabling real-time data exchange with infrastructure, cloud services, and other road users. This ongoing digitalization opens new opportunities to improve road safety through intelligent, context-aware driver assistance systems. Our paper introduces a novel context-aware driver warning system to be developed as part of the ROADGUARD project. The system will fuse data from in-cabin driver monitoring with data about the external driving environment to enhance the accuracy and contextual relevance of safety alerts. Conventional Driver Monitoring Systems (DMS) often rely solely on gaze-based heuristics, which can lead to false positives when environmental context is not considered. Our approach will overcome this limitation by
integrating multimodal sensing, AI-driven edge inference, secure data sharing, and adaptive, multi-target warning delivery. Our proposed system architecture is structured around three interconnected subsystems-Sensing, Sharing, and Acting. It will not only enable more precise, real-time alerts for drivers but also cooperative warnings for vulnerable road users such as pedestrians and cyclists. By embedding situational awareness and supporting data-driven improvement via mobility data spaces, our system supports the Vision Zero objective of eliminating traffic fatalities.
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