Görkem Büyükyildiz, Olivier Pion, Christoph Hildebrandt, M. Sedlmayr, R. Henze, F. Küçükay
{"title":"Identification of the driving style for the adaptation of assistance systems","authors":"Görkem Büyükyildiz, Olivier Pion, Christoph Hildebrandt, M. Sedlmayr, R. Henze, F. Küçükay","doi":"10.1504/IJVAS.2017.10004258","DOIUrl":null,"url":null,"abstract":"Reliable knowledge of specific driver characteristics is important for the adaptation of assistance systems to the driver. The increased safety and comfort based on this knowledge can improve customer acceptance. This study presents a method of identifying specific driver characteristics, i.e. a personal 'fingerprint'. This can be used to draw conclusions about the driving style, age and performance of the driver. To identify the fingerprint, the driver is classified based on the individual driver behaviour, and longitudinal and lateral control behaviour are analysed. The method of identifying the driving style and its implementation into the vehicle using a 'driving style identifier' are the main focuses of this paper. To improve the identifier, lane camera and radar data is taken into account in addition to vehicle signals, such as velocity, longitudinal and lateral acceleration. Several examples of the process of determining the objective parameters from longitudinal and lateral control behaviour are illustrated.","PeriodicalId":39322,"journal":{"name":"International Journal of Vehicle Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Autonomous Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJVAS.2017.10004258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 8
Abstract
Reliable knowledge of specific driver characteristics is important for the adaptation of assistance systems to the driver. The increased safety and comfort based on this knowledge can improve customer acceptance. This study presents a method of identifying specific driver characteristics, i.e. a personal 'fingerprint'. This can be used to draw conclusions about the driving style, age and performance of the driver. To identify the fingerprint, the driver is classified based on the individual driver behaviour, and longitudinal and lateral control behaviour are analysed. The method of identifying the driving style and its implementation into the vehicle using a 'driving style identifier' are the main focuses of this paper. To improve the identifier, lane camera and radar data is taken into account in addition to vehicle signals, such as velocity, longitudinal and lateral acceleration. Several examples of the process of determining the objective parameters from longitudinal and lateral control behaviour are illustrated.