{"title":"Identification of a linear driver model based on simulator experiments","authors":"András Mihály, P. Gáspár","doi":"10.1109/SACI.2014.6840057","DOIUrl":null,"url":null,"abstract":"The paper presents a driver model identification method based on simulator experiments. The visual and vestibular perception of the driver can be modeled by measuring proper signals of the vehicle motion and the environment during the real-time driving of the simulator. The parameters of different drivers are then estimated using a linear difference autoregressive model structure and least-squares estimation techniques. The aim of the identification is to describe the different driver behaviors with the parameters of a driver model with similar structure. The identified driver models are validated by simulation using the same excitation signals as in the simulator experiment and comparing the measured and simulated output of the driver. The main novelty of the paper is the identification method in which a real-time simulator is used.","PeriodicalId":163447,"journal":{"name":"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2014.6840057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
The paper presents a driver model identification method based on simulator experiments. The visual and vestibular perception of the driver can be modeled by measuring proper signals of the vehicle motion and the environment during the real-time driving of the simulator. The parameters of different drivers are then estimated using a linear difference autoregressive model structure and least-squares estimation techniques. The aim of the identification is to describe the different driver behaviors with the parameters of a driver model with similar structure. The identified driver models are validated by simulation using the same excitation signals as in the simulator experiment and comparing the measured and simulated output of the driver. The main novelty of the paper is the identification method in which a real-time simulator is used.