{"title":"Road Sensing with Intelligent Tires for Driving Assistance Applications","authors":"Tong Zhao, M. Kaliske, Yintao Wei","doi":"10.2346/tire.22.22005","DOIUrl":null,"url":null,"abstract":"\n Tires with embedded sensors enable them to be active sensing components. Intelligent tires have increased potential in sensing not only the state of the tire itself but the related properties of the road. This Technical Note briefly describes the application of accelerometer-based intelligent tires in sensing the adhesion level and unevenness of the road. A combined tire longitudinal dynamic model is introduced to estimate the tire-road friction from the waveform features of the acceleration signals. Data-driven methods are adopted to directly classify the road unevenness level from the original signals. Primary analyses and experiments verify the proposed method. Road sensing with intelligent tires contributes to the development of active safety control and driving assistance systems.","PeriodicalId":44601,"journal":{"name":"Tire Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tire Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2346/tire.22.22005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Tires with embedded sensors enable them to be active sensing components. Intelligent tires have increased potential in sensing not only the state of the tire itself but the related properties of the road. This Technical Note briefly describes the application of accelerometer-based intelligent tires in sensing the adhesion level and unevenness of the road. A combined tire longitudinal dynamic model is introduced to estimate the tire-road friction from the waveform features of the acceleration signals. Data-driven methods are adopted to directly classify the road unevenness level from the original signals. Primary analyses and experiments verify the proposed method. Road sensing with intelligent tires contributes to the development of active safety control and driving assistance systems.
期刊介绍：
Tire Science and Technology is the world"s leading technical journal dedicated to tires. The Editor publishes original contributions that address the development and application of experimental, analytical, or computational science in which the tire figures prominently. Review papers may also be published. The journal aims to assure its readers authoritative, critically reviewed articles and the authors accessibility of their work in the permanent literature. The journal is published quarterly by the Tire Society, Inc., an Ohio not-for-profit corporation whose objective is to increase and disseminate knowledge of the science and technology of tires.
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