{"title":"Smart mobility: Algorithm for road and driver type determination","authors":"Pritesh Doshi, Dheeraj Kapur, Ramkumar Iyer, Arkajyoti Chatterjee","doi":"10.1109/ITEC-INDIA.2017.8333895","DOIUrl":null,"url":null,"abstract":"Automotive components and systems during their real world use face different types of drivers, different traffic condition and different road terrains. It is possible to map the vehicle use using GPS (Global Positioning Systems) systems, but it would result in huge pile of data with maps and pose difficulty in terrain mapping, adding to the challenges. Depending on the traffic situation drivers may behave differently on the mapped road sections. Adding technologies and hardware to enable vehicles determine their surrounding environment and react accordingly increases the cost of system. For smart and interconnected vehicle applications, with increased mechatronics and connectivity, determination of the road-type and driver type on the fly helps for optimizing strategies and performance. An algorithm that determines the type of road, using the data available from existing hardware, on which the vehicle is being driven — city, rural, highway, or suburban — and the type of driver — aggressive, economical, or normal — is being developed at Schaeffler. The algorithm also determines and constantly updates the real world duty cycles for different parts of the world. This helps in development and validation of systems for their actual usage.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Transportation Electrification Conference (ITEC-India)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITEC-INDIA.2017.8333895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Automotive components and systems during their real world use face different types of drivers, different traffic condition and different road terrains. It is possible to map the vehicle use using GPS (Global Positioning Systems) systems, but it would result in huge pile of data with maps and pose difficulty in terrain mapping, adding to the challenges. Depending on the traffic situation drivers may behave differently on the mapped road sections. Adding technologies and hardware to enable vehicles determine their surrounding environment and react accordingly increases the cost of system. For smart and interconnected vehicle applications, with increased mechatronics and connectivity, determination of the road-type and driver type on the fly helps for optimizing strategies and performance. An algorithm that determines the type of road, using the data available from existing hardware, on which the vehicle is being driven — city, rural, highway, or suburban — and the type of driver — aggressive, economical, or normal — is being developed at Schaeffler. The algorithm also determines and constantly updates the real world duty cycles for different parts of the world. This helps in development and validation of systems for their actual usage.