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1. 发明授权

US09129519B2 System and method for providing driver behavior classification at intersections and validation on large naturalistic data sets 有权
标题翻译：在交叉点提供驾驶员行为分类的系统和方法以及大型自然数据集的验证
公开(公告)号：US09129519B2
公开(公告)日：2015-09-08
申请号：US13954954
申请日：2013-07-30
申请人： Massachusetts Institute of Technology
发明人： Georges Aoude , Vishnu Rajeswar Desaraju , Jonathan P. How , Thomas Edward Pilutti
IPC分类号： G08G1/00 , G08G1/0962 , G08G1/16
CPC分类号： G08G1/00 , G08G1/0962 , G08G1/162 , G08G1/166
摘要： A system and method for predicting whether a vehicle will come to a stop at an intersection is provided. Generally, the system contains a memory; and a processor configured by the memory to perform the steps of: generating a prediction of whether the vehicle will or will not stop at the intersection before a first time based on vehicle data measured during a first time window; and at a second time, the second time being before the first time and approximately equal to a time at which the time window ends, providing an indication that the vehicle will not stop at the intersection before the first time based upon the prediction, wherein generating the prediction comprises using a classification model, the classification model configured to indicate whether the vehicle will or will not stop at the intersection before the first time based on a plurality of input parameters, and wherein the plurality of input parameters are selected from the group consisting of speed, acceleration, and distance to the intersection.
摘要翻译：提供了一种用于预测车辆是否将在十字路口停下的系统和方法。通常，系统包含一个内存; 以及由所述存储器配置的处理器，用于执行以下步骤：基于在第一时间窗口期间测量的车辆数据，产生车辆是否将在第一时间之前在交叉点停车的预测; 并且在第二时间，第二次是在第一时间之前并且大致等于时间窗口结束的时间，提供基于预测在第一时间之前车辆将不会在交叉路口停止的指示，其中产生所述预测包括使用分类模型，所述分类模型被配置为基于多个输入参数来指示所述车辆是否将在所述第一时间之前在所述十字路口处停车，并且其中所述多个输入参数从以下组中选择：的速度，加速度和到交点的距离。

2. 发明申请

US20140032089A1 SYSTEM AND METHOD FOR PROVIDING DRIVER BEHAVIOR CLASSIFICATION AT INTERSECTIONS AND VALIDATION ON LARGE NATURALISTIC DATA SETS 有权
标题翻译：用于提供驱动程序行为分类的系统和方法，用于大型自然数据集的交互和验证
公开(公告)号：US20140032089A1
公开(公告)日：2014-01-30
申请号：US13954954
申请日：2013-07-30
申请人： Massachusetts Institute of Technology
发明人： Georges Aoude , Vishnu Rajeswar Desaraju , Jonathan P. How , Thomas Edward Pilutti
IPC分类号： G08G1/00
CPC分类号： G08G1/00 , G08G1/0962 , G08G1/162 , G08G1/166
摘要： A system and method for predicting whether a vehicle will come to a stop at an intersection is provided. Generally, the system contains a memory; and a processor configured by the memory to perform the steps of: generating a prediction of whether the vehicle will or will not stop at the intersection before a first time based on vehicle data measured during a first time window; and at a second time, the second time being before the first time and approximately equal to a time at which the time window ends, providing an indication that the vehicle will not stop at the intersection before the first time based upon the prediction, wherein generating the prediction comprises using a classification model, the classification model configured to indicate whether the vehicle will or will not stop at the intersection before the first time based on a plurality of input parameters, and wherein the plurality of input parameters are selected from the group consisting of speed, acceleration, and distance to the intersection.
摘要翻译：提供了一种用于预测车辆是否将在十字路口停下的系统和方法。通常，系统包含一个内存; 以及由所述存储器配置的处理器，用于执行以下步骤：基于在第一时间窗口期间测量的车辆数据，产生车辆是否将在第一时间之前在交叉点停车的预测; 并且在第二时间，第二次是在第一时间之前并且大致等于时间窗口结束的时间，提供基于预测在第一时间之前车辆将不会在交叉路口停止的指示，其中产生所述预测包括使用分类模型，所述分类模型被配置为基于多个输入参数来指示所述车辆是否将在所述第一时间之前在所述十字路口处停车，并且其中所述多个输入参数从以下组中选择：的速度，加速度和到交点的距离。

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