Lane Markings Detection

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Date:28 May, 2016

Lane Markings Detection

    Lane Markings Detection is useful for many different ADAS: to maintain the vehicle on the lane in case of driver’s drowsiness, to detect dangerous lane changes (when combined with back-viewing sensors), to assisting in the steering wheel torque, etc.

    Detection of lane markings based on a camera sensor can be a low cost solution to lane departure warning and lateral control. However, reliable detection is difficult due to cast shadows, vehicles occluding the marks, wear, vehicle motion, etc. In our work we propose to use the ridgeness as a low-level descriptor to detect and characterize the lane markings. RANSAC is used to fit a parametric model to the curvature of the lanes in the image.

    Title: Lane Markings Detection

    Duration: 2002

    Principal Investigator: Antonio M. López 

    Funding: SEAT CT and Volkswagen AG

    Participants: Antonio M. López, Cristina Cañero, Jordi Saludes, Joan Serrat, Felipe Lumbreras

    Related Project

    About us

    Elektra is an autonomous vehicle project developed by research groups from the CVC research center and the UAB and UPC universities.

    Our main objectives are boosting the research in self-driving technology and forming highly qualified engineers.

    Our vision

    We imagine cities with a centralized mobility system to move safely, comfortably, saving energy and minimizing congestion. The city controls a fleet of automated vehicles that cooperate among them and with the city infrastructure.

    Funding

    Our funding mainly comes from public competitive and technological transfer projects.

    We would like to acknowledge to the Spanish project TRA2014-57088-C2-1-R and NVIDIA for the donated hardware.

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