公开(公告)号：US08489317B2

公开(公告)日：2013-07-16

申请号：US12201884

申请日：2008-08-29

Applicant: Derek Stanley Caveney ,  Andrew James Frantz ,  Jeffrey Clark Lovell ,  Lorenzo Caminiti

Inventor： Derek Stanley Caveney ,  Andrew James Frantz ,  Jeffrey Clark Lovell ,  Lorenzo Caminiti

IPC: G06F17/10

CPC classification number: G08G1/161 ,  B60W30/08 ,  B60W2520/10 ,  B60W2520/14 ,  B60W2520/28 ,  B60W2550/402

Abstract: A method for predicting future states of a vehicle including the steps of selecting a model having n states reflecting dynamic features of the vehicle; inputting noisy sensor measurements representing a current state of the vehicle to generate (2n+1) sigma points Xi where i=0, . . . . 2n, each of the sigma points having n states; performing (2n+1) integrations, each integration includes propagating the n-states of the respective sigma points Xi through the non-linear function Yi=f(Xi); and combining the propagated sigma points to generate the predicted future states of the vehicle.

Abstract translation: 一种用于预测车辆的未来状态的方法，包括以下步骤：选择具有反映车辆的动态特征的n个状态的模型; 输入表示车辆的当前状态的噪声传感器测量值，以产生其中i = 0的（2n + 1）个Σ点Xi。 。 。 。 2n，每个Σ点具有n个状态; 执行（2n + 1）积分，每个积分包括通过非线性函数Yi = f（Xi）传播各个Σ点Xi的n态。 并组合传播的σ点以产生车辆的预测未来状态。

公开(公告)号：US20100057361A1

公开(公告)日：2010-03-04

申请号：US12201884

申请日：2008-08-29

Applicant: Derek Stanley CAVENEY ,  Andrew James FRANTZ ,  Jeffrey Clark LOVELL ,  Lorenzo CAMINITI

Inventor： Derek Stanley CAVENEY ,  Andrew James FRANTZ ,  Jeffrey Clark LOVELL ,  Lorenzo CAMINITI

IPC: G08G1/16

CPC classification number: G08G1/161 ,  B60W30/08 ,  B60W2520/10 ,  B60W2520/14 ,  B60W2520/28 ,  B60W2550/402

Abstract: A method for predicting future states of a vehicle including the steps of selecting a model having n states reflecting dynamic features of the vehicle; inputting noisy sensor measurements representing a current state of the vehicle to generate (2n+1) sigma points Xi where i=0, . . . . 2n, each of the sigma points having n states; performing (2n+1) integrations, each integration includes propagating the n-states of the respective sigma points Xi through the non-linear function Yi=f(Xi); and combining the propagated sigma points to generate the predicted future states of the vehicle.

Abstract translation: 一种用于预测车辆的未来状态的方法，包括以下步骤：选择具有反映车辆的动态特征的n个状态的模型; 输入表示车辆的当前状态的噪声传感器测量值，以产生其中i = 0的（2n + 1）个Σ点Xi。 。 。 。 2n，每个Σ点具有n个状态; 执行（2n + 1）积分，每个积分包括通过非线性函数Yi = f（Xi）传播各个Σ点Xi的n态。 并组合传播的σ点以产生车辆的预测未来状态。