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This paper represents the novel high precision localization approach forAutomated Driving (AD) relative to 3D map. The AD maps are not necessarilyflat. Hence, the problem of localization is solved here in 3D. The vehiclemotion is modeled as piecewise planner but with vertical curvature which isapproximated with clothoids. The localization problem is solved withDecentralized Kalman filter with feedback (DKFF) by fusing all availableinformation. The odometry, visual odometry, GPS, the different sensor and monocamera inputs are fused together to obtain the precise localization relative tomap. Polylines and landmarks from the map are dealt in the same way because ofthe line - point geometrical duality. A set of weak filters are accumulated inthe strong tracking approach leading to the precise localization results.

Precise localization relative to 3D Automated Driving map using the Decentralized Kalman filter with Feedback