  This paper represents the novel high precision localization approach for
Automated Driving (AD) relative to 3D map. The AD maps are not necessarily
flat. Hence, the problem of localization is solved here in 3D. The vehicle
motion is modeled as piecewise planner but with vertical curvature which is
approximated with clothoids. The localization problem is solved with
Decentralized Kalman filter with feedback (DKFF) by fusing all available
information. The odometry, visual odometry, GPS, the different sensor and mono
camera inputs are fused together to obtain the precise localization relative to
map. Polylines and landmarks from the map are dealt in the same way because of
the line - point geometrical duality. A set of weak filters are accumulated in
the strong tracking approach leading to the precise localization results.
