In the world of autonomous driving, high resolution maps play a fundamental role. Such maps are highly accurate representations of the environment and are essential for all the algorithms of strategy and path planning operations. Unfortunately, it is not always possible to guarantee the total reliability of these maps and therefore it is necessary to design a procedure for their validation. In this paper we introduce a framework for validating map data at run-time based on probabilistic graphical models. Results from simulations show the capabilities of the proposed approach and highlight the need to find an appropriate balance between model accuracy and complexity.
Use of probabilistic graphical methods for online map validation
Cenedese, Angelo
2021
Abstract
In the world of autonomous driving, high resolution maps play a fundamental role. Such maps are highly accurate representations of the environment and are essential for all the algorithms of strategy and path planning operations. Unfortunately, it is not always possible to guarantee the total reliability of these maps and therefore it is necessary to design a procedure for their validation. In this paper we introduce a framework for validating map data at run-time based on probabilistic graphical models. Results from simulations show the capabilities of the proposed approach and highlight the need to find an appropriate balance between model accuracy and complexity.Pubblicazioni consigliate
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