Vehicle illegal lane change identification method based on two stages

Abstract

The invention discloses a two-stage-based vehicle illegal lane change identification method, which comprises the following steps of: starting a vehicle and a camera, and reading a camera image as input in real time; processing the input image, and detecting a lane line; comparing the change condition of the base points of the lane lines, judging whether the vehicle changes the lane or not and the lane changing direction, if not, reading the image again for recognition, otherwise, intercepting the lane changing lane line image and carrying out the next step; and applying the lane line type prediction model to equipment, identifying a lane changing lane line, and if the identification result is one of a solid line, a solid virtual line or double solid lines, determining illegal lane changing, and giving an alarm prompt. According to the invention, lane lines, vehicle lane change and lane line types of lane change can be identified; a residual module is improved, the recognition precision of an algorithm is improved, lane line detection and recognition can be rapidly completed, and embedded transplantation application is facilitated.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a two-stage-based identification method for vehicles changing lanes illegally. Background technique [0002] In recent years, with the improvement of the popularity of motor vehicles, the contradiction between the rapid growth of automobile sales and the insufficient foundation of road construction has appeared in many countries, which has brought a huge threat to the lives and property safety of the people. According to statistics, about 1.3 million people die in traffic accidents every year in the world, and 80% of traffic accidents are directly or indirectly caused by drivers' mistakes, such as fatigue driving, inattention, bad driving habits, etc., of which about 50% of automobile traffic accidents are caused by vehicles changing lanes illegally. [0003] With the improvement of computer computing power and the acceleration of industrial applic...

AI Technical Summary

Problems solved by technology

In order to solve the problem of few data sets for lane line type recognition, a lane line type recognition data set was created by sorting out public data sets and recording images in actual scenes using existing conditions for training of recognition algorithms

In order to solve the problems of low accuracy of lane marking algorithm and difficulty in embedded application, by analyzing the characteristics of lane marking types and the requirements of embedded transplantation, first use morphological operations to detect lane markings and judge whether there is a lane change. If it exists, extract the front image and enter the lane line recognition; through performance comparison and embedded transplantation speed requirements, the recognition algorithm chooses resnet50 as the basic model, and at the same time, according to the characteristics of the lane line type and resnet50, resnet50 is improved to obtain Higher recognition accuracy

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