Donato Ciurlia
Lane detection to estimate road curvature and vehicle position for an assisted driving vehicle.
Rel. Andrea Tonoli, Nicola Amati, Angelo Bonfitto. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2022
Abstract
Over the last ten years fuel economy (FE) has been improved thanks to the incorporation of a variety of ADAS sensors in hybrid vehicles. ADAS sensors make it possible to estimate road information such as the road slope and the road curvature. The aim of this thesis is the implementation of an advance lane detection algorithm that is able to compute the radius of the road curvature and the vehicle position with respect to the lanes’ centre. Two ADAS sensors are fundamental for this work: lidar and camera. The starting point is the implementation of a lane detection algorithm in 3D point cloud using a lidar sensor.
The proposed Matlab algorithm allows to detect the lane points using the sliding window technique
Relators
Academic year
Publication type
Number of Pages
Additional Information
Course of studies
Classe di laurea
URI
![]() |
Modify record (reserved for operators) |
