LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

by   Ze Wang, et al.

Lane detection is to detect lanes on the road and provide the accurate location and shape of each lane. It severs as one of the key techniques to enable modern assisted and autonomous driving systems. However, several unique properties of lanes challenge the detection methods. The lack of distinctive features makes lane detection algorithms tend to be confused by other objects with similar local appearance. Moreover, the inconsistent number of lanes on a road as well as diverse lane line patterns, e.g. solid, broken, single, double, merging, and splitting lines further hamper the performance. In this paper, we propose a deep neural network based method, named LaneNet, to break down the lane detection into two stages: lane edge proposal and lane line localization. Stage one uses a lane edge proposal network for pixel-wise lane edge classification, and the lane line localization network in stage two then detects lane lines based on lane edge proposals. Please note that the goal of our LaneNet is built to detect lane line only, which introduces more difficulties on suppressing the false detections on the similar lane marks on the road like arrows and characters. Despite all the difficulties, our lane detection is shown to be robust to both highway and urban road scenarios method without relying on any assumptions on the lane number or the lane line patterns. The high running speed and low computational cost endow our LaneNet the capability of being deployed on vehicle-based systems. Experiments validate that our LaneNet consistently delivers outstanding performances on real world traffic scenarios.


page 3

page 4

page 5

page 7


Prediction of Lane Number Using Results From Lane Detection

The lane number that the vehicle is traveling in is a key factor in inte...

Separated RoadTopoFormer

Understanding driving scenarios is crucial to realizing autonomous drivi...

Dense Hybrid Proposal Modulation for Lane Detection

In this paper, we present a dense hybrid proposal modulation (DHPM) meth...

SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility

We present an approach towards robust lane tracking for assisted and aut...

Real time Detection of Lane Markers in Urban Streets

We present a robust and real time approach to lane marker detection in u...

LaNet: Real-time Lane Identification by Learning Road SurfaceCharacteristics from Accelerometer Data

The resolution of GPS measurements, especially in urban areas, is insuff...

Please sign up or login with your details

Forgot password? Click here to reset