Classification of the Condition of Pavement with the Use of Machine Learning Methods

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Pawel Tomilo
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引用次数: 0

Abstract

Abstract The publication includes a review of information on the methods of pavement condition recognition using various methods. Measurement system has been presented that allows to determine the condition of the pavement using the Inertial Measurement Unit (IMU) and machine learning methods. Three machine learning methods were considered: random forest, gradient boosted tree and custom architecture neural network (roadNet). Due to the developed system the set of learning and validation data was created on 3 vehicles: Opel Corsa, Honda Accord, Volkswagen Passat. All of the listed vehicles have front wheel drive. The presented machine learning methods have been compared with each other. The best accuracy on the validation set was achieved by the artificial neural network (ANN). The study showed that asphalt condition classification is possible and the developed system fulfils its task.
使用机器学习方法对路面状况进行分类
摘要该出版物包括使用各种方法对路面状况识别方法的信息的回顾。已经提出了一种测量系统,可以使用惯性测量单元(IMU)和机器学习方法来确定路面状况。考虑了三种机器学习方法:随机森林、梯度增强树和自定义架构神经网络(roadNet)。由于开发的系统,建立了一套学习和验证数据的3辆车:欧宝科萨,本田雅阁,大众帕萨特。所有列出的车辆都有前轮驱动。对所提出的机器学习方法进行了比较。人工神经网络(ANN)在验证集上的准确率最高。研究表明,沥青状态分类是可行的,所开发的系统完成了它的任务。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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