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1. 发明授权

US07044742B2 Emergency reporting apparatus 有权
标题翻译：应急报告装置
公开(公告)号：US07044742B2
公开(公告)日：2006-05-16
申请号：US10328021
申请日：2002-12-26
申请人： Koji Sumiya , Tomoki Kubota , Koji Hori , Kazuaki Fujii
发明人： Koji Sumiya , Tomoki Kubota , Koji Hori , Kazuaki Fujii
IPC分类号： G09B19/14
CPC分类号： G08B25/006 , G08B23/00
摘要： An emergency reporting apparatus is provided which is capable of easily acquiring passenger information necessary at the time of an emergency report and reporting as deputy for a passenger in the case of an emergency. The emergency reporting apparatus, in a training mode, simulates questions from an emergency rescue facility which will be addressed when an emergency situation occurs, and learns and stores the reply contents and response procedures. From the questions and replies, the emergency reporting apparatus automatically acquires the necessary passenger information. Then, the emergency reporting apparatus reports, as a deputy for the user, the passenger information acquired in the training mode when there is no reaction from the user at the time of an actual emergency.
摘要翻译：提供一种应急报告装置，其能够在紧急情况下容易地获取紧急报告时的乘客信息和作为乘客的副驾驶。紧急情况报告装置在训练模式下，模拟紧急救援设施的问题，在发生紧急情况时将对其进行处理，并学习和存储回复内容和响应程序。从提问和答复中，应急报告装置自动获取必要的乘客信息。然后，在实际的紧急情况下，当用户没有反应时，紧急报告装置作为用户的副代表报告在训练模式下获取的乘客信息。

2. 发明授权

US08140241B2 Driving action estimating device, driving support device, vehicle evaluating system, driver model creating device, and driving action determining device 有权
标题翻译：驾驶动作估计装置，驾驶辅助装置，车辆评价系统，驾驶员模型生成装置以及驾驶动作判定装置
公开(公告)号：US08140241B2
公开(公告)日：2012-03-20
申请号：US12087130
申请日：2006-12-27
申请人： Kazuya Takeda , Katunobu Itou , Chiyomi Miyajima , Koji Ozawa , Hirokazu Nomoto , Kazuaki Fujii , Seiichi Suzuki
发明人： Kazuya Takeda , Katunobu Itou , Chiyomi Miyajima , Koji Ozawa , Hirokazu Nomoto , Kazuaki Fujii , Seiichi Suzuki
IPC分类号： B60W40/08 , B60W10/04 , B60W30/16
CPC分类号： B60W40/09 , B60W30/16 , G08G1/166 , G08G1/167
摘要： A driver model with higher precision is created as an evaluation standard for a driving condition in a normal condition. By detecting biometric information of a driver, whether a driver is in a usual condition or not is recognized. Then, data of driving conditions are collected while the driver is driving, and from the driving condition data, a part indicating that the driver operates in a usual condition is extracted to create a driver model. Further, the driver model is created taking only a case of driving in a normal condition as a driving action in normal times based on biometric information of the driver, and hence the driver model becomes more precise and neutral. Further, by using a GMM (Gaussian mixture model) for the driver model, a driver model for each driver can be created easily, and moreover, by calculation to maximize a conditional probability, a driving operation action is easily estimated and outputted.
摘要翻译：创建具有较高精度的驾驶员模型作为正常状态下驾驶状况的评估标准。通过检测驾驶员的生物体信息，识别驾驶员是否处于通常状态。然后，在驾驶员驾驶时收集驾驶状况的数据，从驾驶状态数据中提取表示驾驶员在通常情况下操作的部位，生成驾驶员模型。此外，仅在正常状态下驾驶的情况下作为驾驶动作而在正常时间基于驾驶员的生物体信息生成驾驶员模型，因此驾驶员模型变得更加精确和中立。此外，通过对驱动器模型使用GMM（高斯混合模型），可以容易地创建每个驱动器的驱动器模型，此外，通过计算来最大化条件概率，可以容易地估计和输出驱动操作动作。

3. 发明申请

US20090234552A1 Driving Action Estimating Device, Driving Support Device, Vehicle Evaluating System, Driver Model Creating Device, and Driving Action Determining Device 有权
标题翻译：驾驶行动估计装置，驾驶支援装置，车辆评估系统，驾驶员模型制作装置及驾驶动作确定装置
公开(公告)号：US20090234552A1
公开(公告)日：2009-09-17
申请号：US12087130
申请日：2006-12-27
申请人： Kazuya Takeda , Katunobu Itou , Chiyomi Miyajima , Koji Ozawa , Hirokazu Nomoto , Kazuaki Fujii , Seiichi Suzuki
发明人： Kazuya Takeda , Katunobu Itou , Chiyomi Miyajima , Koji Ozawa , Hirokazu Nomoto , Kazuaki Fujii , Seiichi Suzuki
IPC分类号： B60W40/08 , B60W30/16
CPC分类号： B60W40/09 , B60W30/16 , G08G1/166 , G08G1/167
摘要： A driver model with higher precision is created as an evaluation standard for a driving condition in a normal condition. Further, a driving action is estimated using a driver model which can be created easily and can represent driving characteristics of a driver more precisely.By detecting biometric information of a driver, whether a driver is in a usual condition or not is recognized. Then, data of driving conditions (own vehicle information such as, for example, operation amounts of accelerator, brake, and steering wheel, vehicle speed, inter-vehicle distance, acceleration, and the like) are collected while the driver is driving, and from the driving condition data, a part indicating that the driver operates in a usual condition is extracted to create a driver model. Thus, without making the driver aware, a driver model for normal times can be created automatically. Further, the driver model is created taking only a case of driving in a normal condition as a driving action in normal times based on biometric information of the driver, and hence the driver model becomes more precise and neutral.Further, by using a GMM (Gaussian mixture model) for the driver model, a driver model for each driver can be created easily, and moreover, by calculation to maximize a conditional probability, a driving operation action is easily estimated and outputted.
摘要翻译：创建具有较高精度的驾驶员模型作为正常状态下驾驶状况的评估标准。此外，使用可以容易地创建并且可以更准确地表示驾驶员的驾驶特性的驾驶员模型来估计驾驶动作。通过检测驾驶员的生物体信息，识别驾驶员是否处于通常状态。然后，在驾驶者驾驶时收集行驶状况（本车辆信息，例如加速器，制动器，方向盘的操作量，车速，车辆间距离，加速度等）的数据，以及根据驾驶条件数据，提取指示驾驶员在通常状态下操作的部分以创建驾驶员模型。因此，在不使驱动程序知道的情况下，可以自动创建正常时间的驱动程序模型。此外，仅在正常状态下驾驶的情况下作为驾驶动作而在正常时间基于驾驶员的生物体信息生成驾驶员模型，因此驾驶员模型变得更加精确和中立。此外，通过对驱动器模型使用GMM（高斯混合模型），可以容易地创建每个驱动器的驱动器模型，此外，通过计算来最大化条件概率，可以容易地估计和输出驱动操作动作。

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