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Dynamic matrix and model predictive control for a semi-auto pilot car

机译:半自动试验车的动态矩阵与模型预测控制

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Dynamic matrix and model predictive control in a car aims at vehicle localization in order to avoid collisions by providing computational control for driver assistance whichprevents car crashes by taking control of the car away from the driver on incidences of driver's negligence or distraction. This paper provides ways in which the vehicle's position with reference to the surrounding objects and the vehicle's dynamic movement parameters are synchronized and stored in dynamic matrices with samples at regular instants and hence predict the behavior of the car's surrounding to provide the drivers and the passengers with a driving experience that eliminates any reflex braking or steering reactions and tedious driving in traffic conditions or at junctions.It aims at taking corrective action based on the feedback available from the closed loop system which is recursively accessed by the central controller of the car and it controls the propulsion and steeringand provides a greater restoring force to move the vehicle to a safer region.Our work is towards the development of an application for the DSRC framework (Dedicated Short Range Communication for Inter-Vehicular Communication) by US Department of Traffic (DoT) and DARPA (Defense Advanced Research Projects Agency) and European Commission- funded Project SAVE-U (Sensors and System Architecture for Vulnerable road Users Protection) and is a step towards Intelligent Transportation Systems such as Autonomous Unmanned Ground and Aerial Vehicular systems.
机译:汽车定位的动态矩阵和模型预测控制旨在通过为驾驶员援助提供计算控制来避免碰撞,该驾驶援助通过控制驾驶员的疏忽或分心的驾驶员的驾驶员控制车辆撞击车辆。本文提供了车辆在周围物体的位置和车辆的动态移动参数的方式与常规时刻的样品同步并存储在动态矩阵中,因此预测了汽车周围的行为,以提供司机和乘客一种驾驶经验,可消除任何反射制动或转向反应和交通状况的繁琐驾驶,而在交通条件下驾驶。它的目的是基于由闭环系统可获得的反馈来采取纠正措施,该闭环系统由汽车的中央控制器递归地访问的闭环系统控制推进和转向管道提供更大的恢复力,以将车辆移动到更安全的区域。我们的工作是通过我们的流量部(DOT )和DARPA(国防高级研究项目机构)和欧洲有限公司MMISION-资助的项目SAVE-U(传感器和系统架构,用于易受攻击的道路使用者保护),并且是朝智能运输系统(如自主无人)和空中车辆系统等磁力运输系统的一步。

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