Lane line predicating and early warning method suitable for city road

Abstract

The invention discloses a lane line predicating and early warning method suitable for a city road. According to the method, firstly, down sampling is performed on a collected road image, a detection region of interest is set and grayed, filtering enhancement is performed on the region of interest, edge detection is performed through a Canny operator, binarization is performed on the image after edge detection, then the image is mapped on a Hough plane, and lane lines are extracted through improved Hough conversion; then, parameters of the lane line are predicated by the adoption of a classical Kalman filtering algorithm, a region of interest is established, and the lane lines in the region of interest are fitted through a least square method to obtain the optimal predication value; finally, road surface information and current position information of automobiles are combined to establish a lane line departure warning model based on transverse distance, and therefore departure warning is achieved. The recognition method for the lane lines is good in real-time performance and robustness, according to the lane line departure warning model, calculation is easy, and warning is accurate.

Description

technical field [0001] The invention belongs to the technical field of automobile active safety, and relates to a lane line prediction and early warning method suitable for urban roads. Background technique [0002] With the rapid development of social economy, the number of cars is increasing, which brings convenience to people's life, but also brings frequent traffic accidents. According to statistics, about 10 million people are injured in road traffic accidents worldwide every year, and the economic losses directly caused by these accidents account for about 13% of the world's GDP. According to estimates by the US Federal Highway Administration, about 44% of all fatal highway traffic accidents in the United States in 2002 were related to vehicles leaving their lanes. In order to effectively reduce and avoid the occurrence of lane departure traffic accidents, domestic and foreign research institutions and automobile R&D and manufacturers pay more and more attention to th...

AI Technical Summary

Problems solved by technology

For urban semi-structured roads, due to many factors such as complex and changeable road conditions, defective lane markings, serious pollution, and many road interference signs, the existing algorithms have poor road model adaptability and poor lane line recognizability. High, serious interference and other problems, which lead to low accuracy of lane departure warning

Images