Autonomous vehicles benefit from correct maps to participate in traffic safely, but often maps are not verified before their usage.
We address this problem by providing an approach to verify and repair maps automatically based on a formalization of map specifications in higher-order logic.
Unlike previous work, we provide a collection of map specifications.
We can verify and repair all possible map parts, from geometric to semantic elements, e.g., adjacency relationships, lane types, road boundaries, traffic signs, and intersections.
Due to the modular design of our approach, one can integrate additional logics.
We compare ontologies, answer set programming, and satisfiability modulo theories with our higher-order logic verification algorithm.
Our evaluation shows that our approach can efficiently verify and repair maps from several data sources and of different map sizes.
We provide our tool as part of the CommonRoad Scenario Designer toolbox available at commonroad.in.tum.de.
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Autonomous vehicles benefit from correct maps to participate in traffic safely, but often maps are not verified before their usage.
We address this problem by providing an approach to verify and repair maps automatically based on a formalization of map specifications in higher-order logic.
Unlike previous work, we provide a collection of map specifications.
We can verify and repair all possible map parts, from geometric to semantic elements, e.g., adjacency relationships, lane types, road...
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