公开(公告)号：EP1628180B1

公开(公告)日：2008-11-12

申请号：EP05076729.2

申请日：2005-07-27

Applicant: Delphi Technologies, Inc.

Inventor： Schubert, Peter J. ,  Aeschliman, Chad M. ,  Wiles, Benjamin C.

IPC: G05B23/02

CPC classification number: G05B23/024 ,  G05B23/0281

公开(公告)号：EP1628180A2

公开(公告)日：2006-02-22

申请号：EP05076729.2

申请日：2005-07-27

Applicant: Delphi Technologies, Inc.

Inventor： Schubert, Peter J. ,  Aeschliman, Chad M. ,  Wiles, Benjamin C.

IPC: G05B23/02

CPC classification number: G05B23/024 ,  G05B23/0281

Abstract: An event discrimination methodology executes multiple versions of the same or different event discrimination algorithms (36-42) and logically or arithmetically combines their outputs to distinguish between specified events and non-events (46). One given algorithm is repeatedly executed with different sets of calibration data, or alternately, a number of different algorithms are executed. In cases where the algorithm results are arithmetically combined (60), the weights accorded to each algorithm result are dynamically adjusted based on driver input or vehicle dynamic behavior data to accord highest weight to the algorithm(s) calibrated to identify events associated with the detected driver input or vehicle dynamic behavior (68, 70).

Abstract translation: 事件辨别方法执行相同或不同事件辨别算法的多个版本（36-42），并逻辑或算术结合它们的输出以区分特定事件和非事件（46）。 一个给定的算法用不同组的校准数据重复执行，或者可选地，执行许多不同的算法。 在对算法结果进行算术组合（60）的情况下，基于驾驶员输入或车辆动态行为数据动态调整符合每个算法结果的权重，以使最高权重符合经校准的算法以识别与检测到的相关事件 驾驶员输入或车辆动态行为（68,70）。

公开(公告)号：EP1628180A3

公开(公告)日：2006-05-31

申请号：EP05076729.2

申请日：2005-07-27

Applicant: Delphi Technologies, Inc.

Inventor： Schubert, Peter J. ,  Aeschliman, Chad M. ,  Wiles, Benjamin C.

IPC: G05B23/02

CPC classification number: G05B23/024 ,  G05B23/0281

Abstract: An event discrimination methodology executes multiple versions of the same or different event discrimination algorithms (36-42) and logically or arithmetically combines their outputs to distinguish between specified events and non-events (46). One given algorithm is repeatedly executed with different sets of calibration data, or alternately, a number of different algorithms are executed. In cases where the algorithm results are arithmetically combined (60), the weights accorded to each algorithm result are dynamically adjusted based on driver input or vehicle dynamic behavior data to accord highest weight to the algorithm(s) calibrated to identify events associated with the detected driver input or vehicle dynamic behavior (68, 70).