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    INTERNAL SAFETY SYSTEMS FOR AUTONOMOUS DRIVEN VEHICLES
    5.
    发明申请
    INTERNAL SAFETY SYSTEMS FOR AUTONOMOUS DRIVEN VEHICLES 审中-公开
    用于自动驾驶车辆的内部安全系统

    公开(公告)号：WO2017079236A3

    公开(公告)日：2017-06-22

    申请号：PCT/US2016060037

    申请日：2016-11-02

    Applicant: ZOOX INC

    Inventor： KENTLEY TIMOTHY DAVID ,  GAMARA RACHAD YOUSSEF ,  BEHERE SAGAR

    IPC: B60R21/015 ,  G05D1/00

    CPC classification number: B60R21/01512 ,  B60R21/01546 ,  G05D1/0027 ,  G05D2201/0213 ,  G09B9/04

    Abstract: Systems, apparatus and methods implemented in algorithms, hardware, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement interior active safety systems to protect passengers of the autonomous vehicle during a collision with an object or during evasive maneuvers by the autonomous vehicle, for example. The interior active safety systems may be configured to provide passengers with notice of an impending collision and/or emergency maneuvers by the vehicle by tensioning seat belts prior to executing an evasive maneuver and/or prior to a predicted point of collision.

    Abstract translation: 在算法，硬件，软件，固件，逻辑或电路中实现的系统，设备和方法可以被配置为处理数据和传感输入以确定自主车辆外部的物体（例如另一辆车，行人，道路碎片， 骑自行车者等）可能是自主车辆潜在的碰撞威胁。 例如，自主车辆可以被配置为实施内部主动安全系统以在与物体碰撞期间或者在自主车辆的避让操纵期间保护自主车辆的乘客。 内部主动安全系统可以被配置为在执行回避操纵之前和/或在预测的碰撞点之前通过张紧安全带来向乘客提供即将发生的碰撞和/或车辆的紧急操纵的通知。

    MACHINE-LEARNING SYSTEMS AND TECHNIQUES TO OPTIMIZE TELEOPERATION AND/OR PLANNER DECISIONS
    6.
    发明申请
    MACHINE-LEARNING SYSTEMS AND TECHNIQUES TO OPTIMIZE TELEOPERATION AND/OR PLANNER DECISIONS 审中-公开
    机器学习系统和优化远程操作和/或计划人员决策的技术

    公开(公告)号：WO2017079474A2

    公开(公告)日：2017-05-11

    申请号：PCT/US2016/060384

    申请日：2016-11-03

    Applicant: ZOOX, INC.

    Inventor： LEVINSON, Jesse Sol ,  SIBLEY, Gabriel Thurston ,  REGE, Ashutosh Gajanan

    IPC: G05B17/00

    CPC classification number: G05D1/0022 ,  B60Q1/28 ,  B60Q1/30 ,  G05D1/0027 ,  G05D1/0088 ,  G05D2201/0212 ,  G05D2201/0213 ,  G06N7/005 ,  G06N99/005 ,  G06Q10/00 ,  G08G1/005 ,  G08G1/165 ,  G08G1/166 ,  G08G1/202 ,  H04L41/0816 ,  H04L41/16 ,  H04L67/10 ,  H04L67/12

    Abstract: A system, an apparatus or a process may be configured to implement an application that applies artificial intelligence and/or machine-learning techniques to predict an optimal course of action (or a subset of courses of action) for an autonomous vehicle system (e.g., one or more of a planner of an autonomous vehicle, a simulator, or a teleoperator) to undertake based on suboptimal autonomous vehicle performance and/or changes in detected sensor data (e.g., new buildings, landmarks, potholes, etc.). The application may determine a subset of trajectories based on a number of decisions and interactions when resolving an anomaly due to an event or condition. The application may use aggregated sensor data from multiple autonomous vehicles to assist in identifying events or conditions that might affect travel (e.g., using semantic scene classification). An optimal subset of trajectories may be formed based on recommendations responsive to semantic changes (e.g., road construction).

    Abstract translation: 系统，装置或过程可以被配置为实现应用人工智能和/或机器学习技术来预测最佳行为过程（或行为过程的子集）的应用， 对于自主车辆系统（例如，自主车辆，模拟器或遥控操作者的规划者中的一个或多个）基于次优自主车辆性能和/或检测到的传感器数据（例如，新建筑物，地标， 坑洼等）。 当解决由于事件或条件引起的异常时，应用可以基于多个决定和交互来确定轨迹的子集。 应用程序可以使用来自多个自动车辆的汇总传感器数据来帮助识别可能影响旅行的事件或状况（例如，使用语义场景分类）。 基于响应于语义变化的建议（例如道路建设），可以形成轨迹的最佳子集。

    SIMULATION SYSTEM AND METHODS FOR AUTONOMOUS VEHICLES
    7.
    发明申请
    SIMULATION SYSTEM AND METHODS FOR AUTONOMOUS VEHICLES 审中-公开
    自主车辆的仿真系统和方法

    公开(公告)号：WO2017079229A1

    公开(公告)日：2017-05-11

    申请号：PCT/US2016/060030

    申请日：2016-11-02

    Applicant: ZOOX, INC.

    Inventor： LEVINSON, Jesse, Sol ,  SIBLEY, Gabriel, Thurston ,  REGE, Ashutosh, Gajanan

    IPC: B60W40/02 ,  G06N7/00

    CPC classification number: B60R21/01512 ,  B60R21/01546 ,  G05D1/0027 ,  G05D2201/0213 ,  G09B9/00

    Abstract: Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. More specifically, systems, devices, and methods are configured to simulate navigation of autonomous vehicles in various simulated environments. In particular, a method may include receiving data representing characteristics of a dynamic object, calculating a classification of a dynamic object to identify a classified dynamic object, identifying data representing dynamic-related characteristics associated with the classified dynamic object, forming a data model of the classified dynamic object, simulating a predicted range of motion of the classified dynamic object in a simulated environment to form a simulated dynamic object, and simulating a predicted response of a data representation of a simulated autonomous vehicle.

    Abstract translation: 各种实施例总体上涉及自主车辆和相关联的机械，电气和电子硬件，计算机软件和系统以及有线和无线网络通信，以将自主车队作为服务提供。 更具体地说，系统，设备和方法被配置为模拟自动车辆在各种模拟环境中的导航。 特别地，一种方法可以包括：接收表示动态对象的特性的数据;计算动态对象的分类以识别分类的动态对象;识别表示与分类的动态对象相关联的动态相关特性的数据;形成 分类的动态对象，模拟分类的动态对象在模拟环境中的预测运动范围以形成模拟动态对象，以及模拟模拟自主车辆的数据表示的预测响应。

    MACHINE TO MACHINE TARGETING MAINTAINING POSITIVE IDENTIFICATION
    8.
    发明申请
    MACHINE TO MACHINE TARGETING MAINTAINING POSITIVE IDENTIFICATION 审中-公开
    机械定位维护正确识别

    公开(公告)号：WO2016154477A1

    公开(公告)日：2016-09-29

    申请号：PCT/US2016/024088

    申请日：2016-03-24

    Applicant: AEROVIRONMENT, INC.

    Inventor： PEEBLES, Macdonald John ,  MARTIN, Andrew ,  BAKER, Charles Lawrence ,  WANG, Daisy ,  AGUILAR, Kevin Jay ,  HANNA, Matthew Allen ,  YOUNG, Brian ,  SORNBORGER, Eric ,  AAGAARD, Eric James

    IPC: G01C22/00

    CPC classification number: F41G7/2206 ,  B64C39/024 ,  B64D1/04 ,  B64D1/16 ,  B64D47/08 ,  F41G7/2233 ,  G01C11/06 ,  G05D1/0027 ,  G05D1/0038 ,  G05D1/104

    Abstract: A method of targeting, which involves capturing a first video of a scene about a potential targeting coordinate by a first video sensor (102) on a first aircraft (100); transmitting the first video (232) and associated potential targeting coordinate by the first aircraft; receiving the first video on a first display in communication with a processor, the processor also receiving the potential targeting coordinate; selecting the potential targeting coordinate to be an actual targeting coordinate (226) for a second aircraft (116) in response to viewing the first video on the first display; and guiding a second aircraft toward the actual targeting coordinate; where positive identification of a target (114) corresponding to the actual targeting coordinate is maintained from selection of the actual targeting coordinate.

    Abstract translation: 一种瞄准方法，其涉及通过第一飞行器（100）上的第一视频传感器（102）捕获关于潜在瞄准坐标的场景的第一视频; 通过第一飞行器传输第一视频（232）和相关联的潜在目标坐标; 在与处理器通信的第一显示器上接收第一视频，处理器还接收潜在的目标坐标; 响应于观看第一显示器上的第一视频，为第二飞行器（116）选择潜在的瞄准坐标作为实际瞄准坐标（226） 并引导第二飞机朝向实际瞄准坐标; 其中通过选择实际的瞄准坐标来维持对应于实际瞄准坐标的目标（114）的正面识别。

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