  In this paper, we present a global navigation satellite system (GNSS) aided
LiDAR-visual-inertial scheme, RailLoMer-V, for accurate and robust rail vehicle
localization and mapping. RailLoMer-V is formulated atop a factor graph and
consists of two subsystems: an odometer assisted LiDAR-inertial system (OLIS)
and an odometer integrated Visual-inertial system (OVIS). Both the subsystem
exploits the typical geometry structure on the railroads. The plane constraints
from extracted rail tracks are used to complement the rotation and vertical
errors in OLIS. Besides, the line features and vanishing points are leveraged
to constrain rotation drifts in OVIS. The proposed framework is extensively
evaluated on datasets over 800 km, gathered for more than a year on both
general-speed and high-speed railways, day and night. Taking advantage of the
tightly-coupled integration of all measurements from individual sensors, our
framework is accurate to long-during tasks and robust enough to grievously
degenerated scenarios (railway tunnels). In addition, the real-time performance
can be achieved with an onboard computer.
