Smart mobility: Algorithm for road and driver type determination

Pritesh Doshi, Dheeraj Kapur, Ramkumar Iyer, Arkajyoti Chatterjee
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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.
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智能移动:确定道路和驾驶员类型的算法
在现实世界中,汽车零部件和系统面临着不同类型的驾驶员、不同的交通状况和不同的道路地形。虽然可以使用GPS(全球定位系统)来绘制车辆的地图,但这将导致大量的地图数据,并给地形绘制带来困难,从而增加了挑战。根据交通情况,司机在地图上的路段可能会有不同的行为。增加技术和硬件,使车辆能够确定周围环境并做出相应的反应,这增加了系统的成本。对于智能互联汽车应用,随着机电一体化和连接性的增加,动态确定道路类型和驾驶员类型有助于优化策略和性能。舍弗勒正在开发一种算法,利用现有硬件提供的数据,确定车辆行驶的道路类型——城市、农村、高速公路或郊区——以及驾驶员的类型——激进、经济或普通。该算法还确定并不断更新世界不同地区的真实世界占空比。这有助于开发和验证系统的实际使用情况。
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