Abstract: The car lights not only have lighting functions,but also are important ways for vehicles to communicate with other vehicles while driving.In assisted driving,understanding the light message transmitted by surrounding vehicles accurately is a prerequisite for making correct driving decisions.During daytime driving,due to thechangeble environment,it is difficult to achieve good results in road measurement by matching the lights and then recognizing the lamp language.To this end,in view of the daytime driving situation,this paper proposed a method of light language recognition based on vehicle detection.In this paper,the Adaboost cascade classifier is trained to test the vehicle by using the training method of the updated sample.Based on this,the position distribution feature of the vehicle rear is used to determine the region of interest of the lights.In the RGB color space,a color segmentation algorithm is proposed,which can accurately extract the position of the lamp,judge the lighting state of the lamp on the basis of the region of interest,and eliminate the misdetection of color segmentation algorithm.This paper uses the brightness feature when the lamp is lit.The high-position brake light is used as the recognition condition of the brake light lamp language,and the historical frequency information is used as the recognition condition of the turn signal light,and the recognition of the front taillight light during daytime driving is completed.The experiment uses VS2010 and opencv3.4.9 as the algorithm implementation tool,and uses the actual measured data of the driving recorder provided by SAIC as the test data.After test,the accuracy of classifier recognition in experimental training is 93％.Compared with the traditional Adaboost classifier,the recognition accuracy is improved by about 2%,the average accuracy of the light recognition algorithm is 93％,and the average time of the algorithm is about 53ms.The test results show that the classification training method used in the experiment can improve the detection accuracy slightly,and the light recognition algorithm can accurately identify the brakes,the turn signals and the two kinds of lights simultaneously,and can basically guarantee the real-time performance.

Key words: Assisted driving, Color segmentation, Computer vision, Lamp language recognition, Vehicle detection