Concurrent visual multiple lane detection for autonomous vehicles

This paper proposes a monocular vision solution to simultaneous detection of multiple lanes in navigable regions/urban roads using accumulator voting. Unlike other approaches in literature, this paper first examines the extent of lane parameters required for continuous control of any vehicle manually or autonomously. The accumulator-based algorithm is designed using this fundamental control knowledge to vote for the required lane parameters (position of lanes and steering angle required) in the image plane. The novel accumulator voting scheme is called "Parametric Transform for Multi-lane Detection". This paper not only adapts predictive control in the image plane, but also detects multiple lanes in the scene concurrently in the form of multiple peaks in the accumulator. This method is robust to shadows and invariant to color, texture, and width of the road. Finally, the method is designed for dashed/continuous lines.