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    Managing computational tasks in vehicle context
    41.
    发明授权
    Managing computational tasks in vehicle context 有权

    公开(公告)号：US10705884B2

    公开(公告)日：2020-07-07

    申请号：US16034300

    申请日：2018-07-12

    Applicant: Toyota Jidosha Kabushiki Kaisha

    Inventor： Onur Altintas ,  Takamasa Higuchi ,  Kentaro Oguchi ,  Toru Nakanishi

    IPC: G06F9/455 ,  G06F9/50 ,  G06F9/48

    Abstract: A method receives a computational task; determines a processing resource requirement of the computational task; determines available processing resources of a first temporal vehicular virtual server (TVVS) at a first timestamp, the first TVVS comprising first participant vehicles proximally located relative to one another on a road segment at the first timestamp; determines vehicle movement data of the first participant vehicles; estimates available processing resources of the first TVVS at a second timestamp subsequent to the first timestamp based on the vehicle movement data of the first participant vehicles; determines to execute the computational task on the first TVVS based on the processing resource requirement of the computation task, the available processing resources of the first TVVS at the first timestamp, and the estimated available processing resources of the first TVVS at the second timestamp; and assigns the computational task to the first TVVS to execute the computational task.

    Mitigation of Traffic Oscillation on Roadway
    42.
    发明申请
    Mitigation of Traffic Oscillation on Roadway 审中-公开

    公开(公告)号：US20200168084A1

    公开(公告)日：2020-05-28

    申请号：US16202095

    申请日：2018-11-28

    Applicant: Toyota Jidosha Kabushiki Kaisha

    Inventor： Hao Yang ,  Kentaro Oguchi

    IPC: G08G1/08 ,  G05D1/00 ,  G05D1/02 ,  B60W30/18 ,  G08G1/01 ,  G08G1/052

    Abstract: In an example, a method determines a first controllable vehicle traveling along a mitigation road segment of a roadway and determines a control lane in the mitigation road segment. The control lane includes the first controllable vehicle and is impedible by the first controllable vehicle. The method determines a first open lane in the mitigation road segment and applies a target mitigation speed to the first controllable vehicle in the control lane. The first open lane is adjacent to the control lane in the mitigation road segment and the target mitigation speed is based on a traffic state of the first open lane. The target mitigation speed adjusts a traffic stream that flows through the first open lane to mitigate traffic congestion located downstream of the mitigation road segment.

    Distance Estimation Using Machine Learning
    43.
    发明申请
    Distance Estimation Using Machine Learning 审中-公开

    公开(公告)号：US20200074674A1

    公开(公告)日：2020-03-05

    申请号：US16116417

    申请日：2018-08-29

    Applicant: Toyota Jidosha Kabushiki Kaisha

    Inventor： Rui Guo ,  Babajide Ayinde ,  Hao Sun ,  Kentaro Oguchi

    IPC: G06T7/73 ,  G06T7/50 ,  G06T5/00 ,  G06K9/62 ,  G06K9/00

    Abstract: A method receives a captured image depicting image content including an object, the captured image being captured by an image sensor located at a sensor position; generates, using a trained first machine learning logic, a lighting-corrected image from an imitative simulation image depicting at least a portion of the image content of the captured image in a simulation style associated with an environment simulator; generates, using a trained second machine learning logic, a depth estimation image from the lighting-corrected image, the depth estimation image indicating a relative distance between the object depicted in the captured image and the sensor position of the image sensor; and determines an object position of the object depicted in the captured image based on the depth estimation image.

    Hierarchical Route Generation, Provision, and Selection
    44.
    发明申请
    Hierarchical Route Generation, Provision, and Selection 审中-公开

    公开(公告)号：US20190316919A1

    公开(公告)日：2019-10-17

    申请号：US15951142

    申请日：2018-04-11

    Applicant: TOYOTA JIDOSHA KABUSHIKI KAISHA

    Inventor： Shalini Keshavamurthy ,  BaekGyu Kim ,  Kentaro Oguchi

    IPC: G01C21/34 ,  G08G1/0969 ,  G08G1/0968

    Abstract: An example method receives sensor data of a vehicle at a localized server associated with a particular geographic region that has one or more roadway segments. The vehicle is located in the particular geographic region. The method analyzes the sensor data to determine one or more of a localized lane option and a localized path option for navigating the vehicle and provides the one or more of the lane and the path for navigating the vehicle to a centralized server executing a route planer. The centralized server has data covering a plurality of geographic regions. The method determines a centralized route option including one or more of the localized lane option and the localized path option and provides the centralized route option including the one or more of the localized lane option and the localized path option to a guidance selector of a navigation application of the vehicle for processing.

    Real time driving difficulty categorization
    48.
    发明授权
    Real time driving difficulty categorization 有权

    公开(公告)号：US09686451B2

    公开(公告)日：2017-06-20

    申请号：US14602214

    申请日：2015-01-21

    Applicant: TOYOTA JIDOSHA KABUSHIKI KAISHA

    Inventor： Preeti Jayagopi Pillai ,  Veeraganesh Yalla ,  Kentaro Oguchi ,  Hirokazu Nomoto

    IPC: G06K9/00 ,  H04N5/225 ,  G06K9/46

    CPC classification number: H04N5/225 ,  G06K9/00697 ,  G06K9/00791 ,  G06K9/46 ,  G06T2207/10016

    Abstract: The disclosure includes a system and method for determine a real time driving difficulty category. The method may include determining image feature vector data based on one or more features depicted in a real time image of a road scene. The image feature vector data may describe an image feature vector for an edited version of the real time image. The method may include determining offline road map data for the road scene, which includes a static label for a road included in the road scene and offline road information describing a regulatory speed limit for the road. The method may include selecting, based on the static label, a classifier for analyzing the image feature vector. The method may include executing the selected classifier to determine a real time driving difficulty category describing the difficulty for a user of the client device to drive in the road scene.

    Object Detection and Localized Extremity Guidance
    49.
    发明申请
    Object Detection and Localized Extremity Guidance 有权
    对象检测和局部化肢体指导

    公开(公告)号：US20160267755A1

    公开(公告)日：2016-09-15

    申请号：US14658138

    申请日：2015-03-13

    Applicant: TOYOTA JIDOSHA KABUSHIKI KAISHA

    Inventor： Eric Martinson ,  Emrah Akin Sisbot ,  Joseph Djugash ,  Kentaro Oguchi ,  Yutaka Takaoka ,  Yusuke Nakano

    IPC: G08B6/00

    CPC classification number: G08B6/00

    Abstract: Technology for localized guidance of a body part of a user to specific objects within a physical environment using a vibration interface is described. An example system may include a vibration interface wearable on an extremity by a user. The vibration interface includes a plurality of motors. The system includes sensor(s) coupled to the vibrotactile system and a sensing system coupled to the sensor(s) and the vibration interface. The sensing system is configured to analyze a physical environment in which the user is located for a tangible object using the sensor(s), to generate a trajectory for navigating the extremity of the user to the tangible object based on a relative position of the extremity of the user bearing the vibration interface to a position of the tangible object within the physical environment, and to guide the extremity of the user along the trajectory by vibrating the vibration interface.

    Abstract translation: 引导使用振动界面的物理环境中用户身体部位进行局部引导的技术被描述。 示例性系统可以包括由用户在肢体上佩戴的振动界面。 振动界面包括多个电动机。 该系统包括耦合到振动脉冲系统的传感器和耦合到传感器和振动界面的感测系统。 感测系统被配置为使用传感器来分析用户对于有形物体的物理环境，以基于肢体的相对位置生成用于将用户的末端导航到有形物体的轨迹 承载振动界面的用户到物理环境中的有形物体的位置，并且通过振动振动界面来引导使用者的沿着轨迹的末端。

    REAL TIME DRIVING DIFFICULTY CATEGORIZATION
    50.
    发明申请
    REAL TIME DRIVING DIFFICULTY CATEGORIZATION 有权
    实时驱动困难分类

    公开(公告)号：US20160207458A1

    公开(公告)日：2016-07-21

    申请号：US14602214

    申请日：2015-01-21

    Applicant: TOYOTA JIDOSHA KABUSHIKI KAISHA

    Inventor： Preeti Jayagopi Pillai ,  Veeraganesh Yalla ,  Kentaro Oguchi ,  Hirokazu Nomoto

    IPC: B60R1/00 ,  H04N5/225 ,  G06K9/46 ,  G06K9/00 ,  G06T7/00

    CPC classification number: H04N5/225 ,  G06K9/00697 ,  G06K9/00791 ,  G06K9/46 ,  G06T2207/10016

    Abstract: The disclosure includes a system and method for determine a real time driving difficulty category. The method may include determining image feature vector data based on one or more features depicted in a real time image of a road scene. The image feature vector data may describe an image feature vector for an edited version of the real time image. The method may include determining offline road map data for the road scene, which includes a static label for a road included in the road scene and offline road information describing a regulatory speed limit for the road. The method may include selecting, based on the static label, a classifier for analyzing the image feature vector. The method may include executing the selected classifier to determine a real time driving difficulty category describing the difficulty for a user of the client device to drive in the road scene.

    Abstract translation: 本公开包括用于确定实时驾驶难度类别的系统和方法。 该方法可以包括基于道路场景的实时图像中描绘的一个或多个特征来确定图像特征向量数据。 图像特征向量数据可以描述实时图像的编辑版本的图像特征向量。 该方法可以包括确定用于道路场景的离线道路地图数据，其包括道路场景中包括的道路的静态标签和描述道路的监管速度限制的离线道路信息。 该方法可以包括基于静态标签来选择用于分析图像特征向量的分类器。 该方法可以包括执行所选择的分类器以确定描述客户端设备的用户在道路场景中驾驶的难度的实时驾驶难度类别。

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