The driverless car based on the online learning platform realizes the red light recognition and lane line recognition

Fengpeng Guo, Hongcheng Huang, Liangren Shi, Yanbo Liu, Han Zhang
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Abstract

This paper describes how to use online learning platform for traffic light identification, as well as including lane-line identification. First, the traditional traffic light and lane-line identification method were explained; then explaining the concept of neural network and its application in driverless car field; finally, the paper explains how to use the learning platform on the line to train, which can get outputs the model. Using the model, we will get the corresponding results. Based on the continuous optimization of previous studies, this paper makes full use of the advantages of online learning platforms to improve learning methods, to some extent, which enables students to broaden their minds and understand the important position of deep learning in the field of unmanned driving.
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基于在线学习平台的无人驾驶汽车实现了红灯识别和车道线识别
本文介绍了如何利用在线学习平台进行交通灯识别,包括车道-线路识别。首先,阐述了传统的交通灯和车道线识别方法;然后阐述了神经网络的概念及其在无人驾驶汽车领域的应用;最后,阐述了如何利用在线学习平台进行训练,从而得到输出的模型。利用该模型,我们将得到相应的结果。本文在不断优化前人研究的基础上,充分利用在线学习平台的优势,改进学习方法,在一定程度上使学生开阔了视野,了解了深度学习在无人驾驶领域的重要地位。
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