Camera and three-dimensional laser radar data fusion road edge detection method

Abstract

The invention discloses a camera and three-dimensional laser radar data fusion-based road edge detection method. The method comprises the following steps of 1) establishing a grid map by taking a three-dimensional laser radar as an original point; 2) extracting lane line feature points through a camera by adopting an existing method, and measuring transverse and longitudinal distances of the feature points relative to an original point of the camera on an actual road; 3) acquiring road edge candidate points by using a method based on adjacent point height difference characteristics, 4) projecting the lane line feature points to a grid map according to the position relationship between the camera and the laser radar, and fitting by using a quadratic curve model, 5) judging the road edge candidate points within a fixed distance threshold from the lane line curve as road edge points, and 6) filtering the road edge points by using an RANSAC algorithm, and fitting the road edge points in combination with a quadratic curve model. The method can improve detection accuracy of the road edge, and thereby the accurate and reliable road boundary information is provided for the unmanned vehicle, and the occurrence rate of road traffic accidents is reduced.

Description

technical field [0001] The invention belongs to the field of intelligent traffic road environment perception, and in particular relates to a roadside detection method for fusion of camera and three-dimensional laser radar data. Background technique [0002] In recent years, the number of cars and drivers in my country has increased year by year, and the transportation industry has continued to develop. At the same time, the total number of traffic accidents has increased year by year. Cars have been closely linked with people's lives. In order to reduce the death rate caused by traffic accidents, research on unmanned vehicles has attracted more and more attention. In intelligent transportation, unmanned vehicles can accurately perceive the environment in real time and provide drivers with more environmental information, thereby reducing the frequency of traffic accidents. [0003] Road boundary detection is an important part of environment perception. Road color, road surfa...

AI Technical Summary

Problems solved by technology

The camera has a high amount of information but cannot provide accurate three-dimensional information. Although the lidar can obtain accurate three-dimensional information, the point cloud is discrete. Due to the influence of obstacles in the road environment, many false positive roadside points are detected.

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