首页> 外国专利> SYSTEMS AND METHODS FOR UTILIZING MACHINE LEARNING AND FEATURE SELECTION TO CLASSIFY DRIVING BEHAVIOR

SYSTEMS AND METHODS FOR UTILIZING MACHINE LEARNING AND FEATURE SELECTION TO CLASSIFY DRIVING BEHAVIOR

机译:用于利用机器学习和特征选择来对驾驶行为进行分类的系统和方法

摘要

A device may receive vehicle operation data associated with operation of a plurality of vehicles, and may process the vehicle operation data to generate processed vehicle operation data. The device may extract multiple features from the processed vehicle operation data, and may train machine learning models, with the multiple features, to generate trained machine learning models that provide model outputs. The device may process the multiple features, with a feature selection model and based on the model outputs, to select sets of features from the plurality of features, and may process the sets of features, with the trained machine learning models, to generate indications of driving behavior and reliabilities of the indications. The device may select a set of features, from the sets of features, based on the indications and the reliabilities, where the set of features may be calculated by a device associated with a particular vehicle.
机译:设备可以接收与多个车辆的操作相关联的车辆操作数据,并且可以处理车辆操作数据以产生处理的车辆操作数据。该设备可以从处理的车辆操作数据中提取多个特征,并且可以将机器学习模型与多个功能一起培训,以生成提供型号输出的培训的机器学习模型。该设备可以处理多个特征,具有特征选择模型并基于模型输出,以从多个特征中选择一组特征,并且可以使用经过培训的机器学习模型来处理特征集,以生成指示驾驶适应症的行为和可靠性。该设备可以根据指示和可靠性地从特征组中选择一组特征,其中可以通过与特定车辆相关联的设备来计算该组特征集。

著录项

获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号