The ability of autonomous vehicles to maintain an accurate trajectory within
their road lane is crucial for safe operation. This requires detecting the road
lines and estimating the car relative pose within its lane. Lateral lines are
usually retrieved from camera images. Still, most of the works on line
detection are limited to image mask retrieval and do not provide a usable
representation in world coordinates. What we propose in this paper is a
complete perception pipeline based on monocular vision and able to retrieve all
the information required by a vehicle lateral control system: road lines
equation, centerline, vehicle heading and lateral displacement. We evaluate our
system by acquiring data with accurate geometric ground truth. To act as a
benchmark for further research, we make this new dataset publicly available at
http://airlab.deib.polimi.it/datasets/.Comment: Presented at 2020 IEEE Intelligent Vehicles Symposium (IV), 8 pages,
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