公开(公告)号：WO2017079341A2

公开(公告)日：2017-05-11

申请号：PCT/US2016/060173

申请日：2016-11-02

Applicant: ZOOX, INC.

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

IPC: G08G1/056

CPC classification number: G06N7/005 ,  B60W40/04 ,  B60W40/06 ,  G05D1/0088 ,  G05D1/0248 ,  G05D1/0274 ,  G05D2201/0213 ,  G06K9/00 ,  G06K9/00362 ,  G06K9/00805 ,  G06N99/005

Abstract: Systems, methods and apparatus may be configured to implement automatic semantic classification of a detected object(s) disposed in a region of an environment external to an autonomous vehicle. The automatic semantic classification may include analyzing over a time period, patterns in a predicted behavior of the detected object(s) to infer a semantic classification of the detected object(s). Analysis may include processing of sensor data from the autonomous vehicle to generate heat maps indicative of a location of the detected object(s) in the region during the time period. Probabilistic statistical analysis may be applied to the sensor data to determine a confidence level in the inferred semantic classification. The inferred semantic classification may be applied to the detected object(s) when the confidence level exceeds a predetermined threshold value (e.g., greater than 50%).

Abstract translation: 系统，方法和设备可以被配置为实现布置在自主车辆外部的环境的区域中的检测到的物体的自动语义分类。 自动语义分类可以包括在时间段上分析检测到的对象的预测行为中的模式以推断所检测到的对象的语义分类。 分析可以包括处理来自自主车辆的传感器数据以生成指示在该时间段期间在该区域中检测到的物体的位置的热图。 可以将概率统计分析应用于传感器数据以确定推断的语义分类中的置信度水平。 当置信水平超过预定阈值（例如，大于50％）时，可以将推断的语义分类应用于检测到的对象。

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。

公开(公告)号：WO2019182782A1

公开(公告)日：2019-09-26

申请号：PCT/US2019/021553

申请日：2019-03-11

Applicant: ZOOX, INC.

Inventor： LEVINSON, Jesse Sol ,  REGE, Ashutosh Gajanan ,  REBSAMEN, Brice ,  STUMM, Elena ,  SHROFF, Nitesh ,  ADAMS, Derek

IPC: G06T15/80 ,  G06K9/00

Abstract: Techniques for generating maps without shadows are discussed herein. A plurality of images can be captured by a vehicle traversing an environment representing various perspectives and/or lighting conditions in the environment. A shadow within an image can be identified by a machine learning algorithm trained to detect shadows in images and/or by projecting the image onto a three-dimensional (3D) map of the environment and identifying candidate shadow regions based on the geometry of the 3D map and the location of the light source. Shadows can be removed or minimized by utilizing blending or duplicating techniques. Color information and reflectance information can be added to the 3D map to generate a textured 3D map. A textured 3D map without shadows can be used to simulate the environment under different lighting conditions.

公开(公告)号：WO2018160486A1

公开(公告)日：2018-09-07

申请号：PCT/US2018/019685

申请日：2018-02-26

Applicant: ZOOX, INC.

Inventor： LINSCOTT, Gary ,  SOMERS, Robert, Edward ,  KIISKI, Joona Markus Petteri ,  KOBILAROV, Marin ,  CALDWELL, Timothy ,  ASKELAND, Jacob, Lee ,  REGE, Ashutosh Gajanan ,  FUNKE, Joseph

IPC: G05D1/02

Abstract: Techniques for generating and executing trajectories to guide autonomous vehicles are described. In an example, a first computer system associated with an autonomous vehicle can generate, at a first operational frequency, a route to guide the autonomous vehicle from a current location to a target location. The first computer system can further determine, at a second operational frequency, an instruction for guiding the autonomous vehicle along the route and can generate, at a third operational frequency, a trajectory based at least partly on the instruction and real-time processed sensor data. A second computer system that is associated with the autonomous vehicle and is in communication with the first computer system can execute, at a fourth operational frequency, the trajectory to cause the autonomous vehicle to travel along the route. The separation of the first computer system and the second computer system can provide enhanced safety, redundancy, and optimization.

公开(公告)号：WO2021061488A1

公开(公告)日：2021-04-01

申请号：PCT/US2020/051271

申请日：2020-09-17

Applicant: ZOOX, INC.

Inventor： BAGSCHIK, Gerrit ,  CREGO, Andrew Scott ,  DEUX, Antoine Ghislain ,  LYASOFF, Rodin ,  PHILBIN, James William Vaisey ,  WIMMERSHOFF, Marc ,  RESCHKA, Andreas Christian ,  REGE, Ashutosh Gajanan ,  MODALAVALASA, Sai Anurag

IPC: B60W30/08 ,  B60W40/02 ,  B60W60/00 ,  G08G1/16

Abstract: Techniques for determining a safety metric associated with a vehicle controller are discussed herein. To determine whether a complex system (which may be uninspectable) is able to operate safely, various operating regimes (scenarios) can be identified based on operating data and associated with a scenario parameter to be adjusted. To validate safe operation of such a system, a scenario may be identified for inspection. Error metrics of a subsystem of the system can be quantified. The error metrics, in addition to stochastic errors of other systems/subsystems can be introduced to the scenario. The scenario parameter may also be perturbed. Any multitude of such perturbations can be instantiated in a simulation to test, for example, a vehicle controller. A safety metric associated with the vehicle controller can be determined based on the simulation, as well as causes for any failures.

公开(公告)号：WO2019010128A8

公开(公告)日：2019-01-10

申请号：PCT/US2018/040599

申请日：2018-07-02

Applicant: ZOOX, INC.

Inventor： LOCKWOOD, Amanda Lee Kelly ,  GOGNA, Ravi ,  LINSCOTT, Gary ,  CALDWELL, Timothy ,  KOBILAROV, Marin ,  ORECCHIO, Paul ,  XIE, Dan ,  REGE, Ashutosh Gajanan ,  LEVINSON, Jesse Sol

IPC: G05D1/02 ,  G05D1/00

Abstract: A method for operating a driverless vehicle may include receiving, at the driverless vehicle, sensor signals related to operation of the driverless vehicle, and road network data from a road network data store. The method may also include determining a driving corridor within which the driverless vehicle travels according to a trajectory, and causing the driverless vehicle to traverse a road network autonomously according to a path from a first geographic location to a second geographic location. The method may also include determining that an event associated with the path has occurred, and sending communication signals to a teleoperations system including a request for guidance and one or more of sensor data and the road network data. The method may include receiving, at the driverless vehicle, teleoperations signals from the teleoperations system, such that the vehicle controller determines a revised trajectory based at least in part on the teleoperations signals.