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A PHYSICAL MODEL AND MACHINE LEARNING COMBINED METHOD TO SIMULATE AUTONOMOUS VEHICLE MOVEMENT

机译:一种模拟车辆自主运动的物理模型与机器学习相结合的方法

摘要

In one embodiment, a driving scenario is identified for a next movement for an autonomous vehicle, where the driving scenario is represented by a set of one or more predetermined parameters. A first next movement is calculated for the autonomous vehicle using a physical model corresponding to the driving scenario. A sideslip predictive model is applied to the set of predetermined parameters to predict a sideslip of the autonomous vehicle under the driving scenario. A second next movement of the autonomous vehicle is determined based on the first next movement and the predicted sideslip of the autonomous vehicle. The predicted sideslip is utilized to modify the first next movement to compensate the sideslip. Planning and control data is generated for the second next movement and the autonomous vehicle is controlled and driven based on the planning and control data.
机译:在一个实施例中,为自动驾驶车辆的下一动作识别驾驶情景,其中驾驶情景由一组一个或多个预定参数表示。使用与驾驶场景相对应的物理模型为自动驾驶汽车计算出第一下一个运动。将侧滑预测模型应用于该组预定参数,以预测在驾驶情况下自动驾驶车辆的侧滑。基于自动驾驶汽车的第一下一次运动和预测的侧滑来确定自动驾驶汽车的第二下一次运动。预测的侧滑用于修改第一个下一个运动以补偿侧滑。产生用于第二下一动作的计划和控制数据,并且基于该计划和控制数据来控制和驾驶自动驾驶汽车。

著录项

  • 公开/公告号EP3345086B1

    专利类型

  • 公开/公告日2019-11-20

    原文格式PDF

  • 申请/专利权人 BAIDU USA LLC;

    申请/专利号EP20170847785

  • 发明设计人 ZHU FAN;KONG QI;YANG GUANG;WANG JINGAO;

    申请日2017-01-18

  • 分类号G08G1/16;B60W50;B60W30/045;B60W30/18;G05D1/02;

  • 国家 EP

  • 入库时间 2022-08-21 11:40:13

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