Paper Info
Title
Towards Cognitive Vehicles: GNSS-free Localization using Visual Anchors
Abstract
Cognitive vehicles (CV) differ from smart vehicles (SV) in a way that they don't just rely on the sensors' readings and follow rigorously the patterns and functions already preprogrammed externally. CVs utilize the different sensors as a source of information, which needs to be processed and turned into intelligence and perception. CVs learn at a scale, make assumptions, predict outcomes, and learn from experience rather than being explicitly programmed. In this work, we attempt to present a model that duplicates the cognitive process through which humans can self-localize. We present an innovative GNSS-free solution for vehicle self-localization based on detection pattern recognition of visual anchors. The proposed cognitive approach is successfully tested in different routes taken from a real urban environment. The system location estimates are compared with the GPS reported locations and show promising performances.
Year
DOI
Venue
2020
10.23919/FUSION45008.2020.9190496
2020 IEEE 23rd International Conference on Information Fusion (FUSION)
Keywords
DocType
ISBN
Cognitve Vehicles,GNSS-free Localization,Real-time Object Detection,YOLO,Neural Networks,Speed Estimation
Conference
978-1-7281-6830-2
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
Abdessattar Hayouni100.34
Benoit Debaque2102.02
Nicolas Duclos-hindie321.77
Mihai Cristian Florea4777.09