Lane-level HD maps are crucial for trajectory planning and control in current autonomous vehicles. For this reason, appropriate line models should be adopted to define them. Whereas mapping algorithms often rely on inaccurate representations, clothoid curves possess peculiar smoothness properties that make them desirable representations of road lines in control algorithms. We propose a multi-stage pipeline for the generation of lane-level HD maps from monocular vision relying on clothoidal spline models. We obtain measurements of the line positions using a line detection algorithm, and we exploit a graph-based optimization framework to reach an optimal fitting. An iterative greedy procedure reduces the model complexity removing unnecessary clothoids. We validate our system on a real-world dataset, which we make publicly available for further research at https://airlab.deib.polimi.it/datasets-and-tools/.
Clothoidal Mapping of Road Line Markings for Autonomous Driving High-Definition Maps
2022 IEEE Intelligent Vehicles Symposium (IV) ; 1631-1638
2022-06-05
2427915 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Self-driving system for smart road markings and smart road markings
Europäisches Patentamt | 2022
|High performance road markings
British Library Online Contents | 1994
|Lane Line Creation for High Definition Maps for Autonomous Vehicles
Europäisches Patentamt | 2018
|LANE LINE CREATION FOR HIGH DEFINITION MAPS FOR AUTONOMOUS VEHICLES
Europäisches Patentamt | 2021
|