公开(公告)号：US20230182782A1

公开(公告)日：2023-06-15

申请号：US17550996

申请日：2021-12-14

Applicant: Zoox, Inc.

Inventor： Linjun Zhang ,  Marin Kobilarov

IPC: B60W60/00

CPC classification number: B60W60/0027 ,  B60W2554/404 ,  B60W2554/801 ,  B60W2554/802 ,  B60W2554/4042 ,  B60W2554/4043 ,  B60W2520/10 ,  B60W2520/12 ,  B60W2555/60

Abstract: This disclosure is directed to techniques for identifying relevant objects within an environment. For instance, a vehicle may use sensor data to determine a candidate trajectory associated with the vehicle and a predicted trajectory associated with an object. The vehicle may then use the candidate trajectory and the predicted trajectory to determine an interaction between the vehicle and the object. Based on the interaction, the vehicle may determine a time difference between when the vehicle is predicted to arrive at a location and when the object is predicted to arrive at the location. The vehicle may then determine a relevance score associated with the object using the time difference. Additionally, the vehicle may determine whether to input object data associated with the object into a planner component based on the relevance score. The planner component determines one or more actions for the vehicle to perform.

公开(公告)号：US20230051486A1

公开(公告)日：2023-02-16

申请号：US17977770

申请日：2022-10-31

Applicant: Zoox, Inc.

Inventor： Zhenqi Huang ,  Janek Hudecek ,  Marin Kobilarov ,  Dhanushka Nirmevan Kularatne ,  Mark Jonathon McClelland

IPC: B60W60/00 ,  G01S19/39 ,  G01C21/34 ,  G01C21/36 ,  G01S19/42 ,  G01S19/52 ,  G05D1/02

Abstract: The techniques discussed herein may comprise an autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a static object map and/or one or more dynamic object maps. The guidance system may identify a path based at least in part on determining set of nodes and a cost map associated with the static and/or dynamic object, among other costs, pruning the set of nodes, and creating further nodes from the remaining nodes until a computational or other limit is reached. The path output by the techniques may be associated with a cheapest node of the sets of nodes that were generated.

公开(公告)号：US11360477B2

公开(公告)日：2022-06-14

申请号：US16908389

申请日：2020-06-22

Applicant: Zoox, Inc.

Inventor： Marin Kobilarov ,  Timothy Caldwell ,  Vasumathi Raman ,  Christopher Paxton ,  Joona Markus Petteri Kiiski ,  Jacob Lee Askeland ,  Robert Edward Somers

IPC: G05D1/00 ,  B60W30/09 ,  G05D1/02 ,  G01C21/34 ,  G06N3/04 ,  G06N3/08

Abstract: Techniques for determining a trajectory for an autonomous vehicle are described herein. In general, determining a route can include utilizing a search algorithm such as Monte Carlo Tree Search (MCTS) to search for possible trajectories, while using temporal logic formulas, such as Linear Temporal Logic (LTL), to validate or reject the possible trajectories. Trajectories can be selected based on various costs and constraints optimized for performance. Determining a trajectory can include determining a current state of the autonomous vehicle, which can include determining static and dynamic symbols in an environment. A context of an environment can be populated with the symbols, features, predicates, and LTL formula. Rabin automata can be based on the LTL formula, and the automata can be used to evaluate various candidate trajectories. Nodes of the MCTS can be generated and actions can be explored based on machine learning implemented as, for example, a deep neural network.

公开(公告)号：US11142188B2

公开(公告)日：2021-10-12

申请号：US16732087

申请日：2019-12-31

Applicant: Zoox, Inc.

Inventor： Joseph Funke ,  Steven Cheng Qian ,  Marin Kobilarov

IPC: B60W30/06 ,  G01C21/16 ,  G08G1/14 ,  G01C21/34 ,  G05D1/02

Abstract: Techniques for controlling a vehicle on and off a route structure in an environment are discussed herein. A vehicle computing system controls the vehicle along a route based on a route-based reference system. The vehicle computing system may determine to operate off the route, such as to operate in reverse, park, etc. The vehicle computing system may modify vehicle operations to an inertial-based reference system to navigate to a location off the route. The vehicle computing system may determine a vehicle trajectory to the location off the route based on a reference trajectory between a location on the route and the location off the route and a corridor associated therewith. The vehicle computing system may transition between the route-based reference system and the inertial-based reference system, based on a determination to operate on or off the route.

公开(公告)号：US11126180B1

公开(公告)日：2021-09-21

申请号：US16399743

申请日：2019-04-30

Applicant: Zoox, Inc.

Inventor： Marin Kobilarov

IPC: G05D1/00 ,  G05D1/02 ,  G05B13/02

Abstract: Techniques are discussed for predicting occluded regions along a trajectory in an environment, a probability of occupancy associated with the predicted occluded regions, and controlling a vehicle to minimize occlusions and/or probabilities of occupancy. A vehicle may capture sensor data. Portions of an environment may be occluded by an object and may not be represented in the sensor data, and may be referred to as occluded regions. A candidate trajectory can be received and vehicle motion can be simulated to determine predicted occluded regions associated with the candidate trajectory. Data representing a predicted environment can be input to a machine learned model that can output information associated with the predicted occluded regions, such as a probability that the region is occupied by a vehicle or a pedestrian, for example. The candidate trajectory can be evaluated based on such probabilities, and the vehicle can be controlled based on the candidate trajectory.

公开(公告)号：US11126178B2

公开(公告)日：2021-09-21

申请号：US16251788

申请日：2019-01-18

Applicant: Zoox, Inc.

Inventor： Abishek Krishna Akella ,  Janek Hudecek ,  Marin Kobilarov ,  Marc Wimmershoff

IPC: G05D1/00 ,  B60W30/16 ,  B60W30/165 ,  G05D1/02 ,  G06K9/00

Abstract: Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

公开(公告)号：US11023749B2

公开(公告)日：2021-06-01

申请号：US16504147

申请日：2019-07-05

Applicant: Zoox, Inc.

Inventor： Gowtham Garimella ,  Marin Kobilarov ,  Andres Guillermo Morales Morales ,  Kai Zhenyu Wang

IPC: G06K9/00 ,  G06K9/62 ,  G08G1/04 ,  G08G1/01 ,  G06T11/60 ,  G08G1/052 ,  G08G1/056 ,  G05B13/02

Abstract: Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

公开(公告)号：US10829149B1

公开(公告)日：2020-11-10

申请号：US15841260

申请日：2017-12-13

Applicant: Zoox, Inc.

Inventor： Gowtham Garimella ,  Joseph Funke ,  Chuang Wang ,  Marin Kobilarov

IPC: B62D6/00 ,  G05D1/02 ,  G05D1/00 ,  B62D5/04

Abstract: Model-based control of dynamical systems typically requires accurate domain-specific knowledge and specifications system components. Generally, steering actuator dynamics can be difficult to model due to, for example, an integrated power steering control module, proprietary black box controls, etc. Further, it is difficult to capture the complex interplay of non-linear interactions, such as power steering, tire forces, etc. with sufficient accuracy. To overcome this limitation, a recurring neural network can be employed to model the steering dynamics of an autonomous vehicle. The resulting model can be used to generate feedforward steering commands for embedded control. Such a neural network model can be automatically generated with less domain-specific knowledge, can predict steering dynamics more accurately, and perform comparably to a high-fidelity first principle model when used for controlling the steering system of a self-driving vehicle.

公开(公告)号：US20200225659A1

公开(公告)日：2020-07-16

申请号：US16834582

申请日：2020-03-30

Applicant: Zoox, Inc.

Inventor： Amanda Lee Kelly Lockwood ,  Ravi Gogna ,  Gary Linscott ,  Timothy Caldwell ,  Marin Kobilarov ,  Paul Orecchio ,  Dan Xie ,  Ashutosh Gajanan Rege ,  Jesse Sol Levinson

IPC: G05D1/00 ,  G05D1/02 ,  G08G1/16 ,  B60W30/095 ,  G08G1/00

Abstract: A method for autonomously operating a driverless vehicle along a path between a first geographic location and a destination may include receiving communication signals from the driverless vehicle. The communication signals may include sensor data from the driverless vehicle and data indicating occurrence of an event associated with the path. The communication signals may also include data indicating that a confidence level associated with the path is less than a threshold confidence level due to the event. The method may also include determining, via a teleoperations system, a level of guidance to provide the driverless vehicle based on data associated with the communication signals, and transmitting teleoperations signals to the driverless vehicle. The teleoperations signals may include guidance to operate the driverless vehicle according to the determined level of guidance, so that a vehicle controller maneuvers the driverless vehicle to avoid, travel around, or pass through the event.

公开(公告)号：US10671075B1

公开(公告)日：2020-06-02

申请号：US15843512

申请日：2017-12-15

Applicant: Zoox, Inc.

Inventor： Marin Kobilarov

IPC: G05D1/02 ,  G05D1/00 ,  G01C21/34 ,  G06K9/00

Abstract: A trajectory for an autonomous vehicle (AV) can be generated using curvature segments. A decision planner component can receive a reference trajectory for the AV to follow in an environment. A number of subdivisions (frames) of the reference trajectory may be associated with a curvature value and a tangent vector. Starting with an initial position of the AV, a candidate trajectory can be determined by continuously intersecting a segment with an origin at the initial position of the AV and a reference line associated with a particular frame. The reference line can be substantially perpendicular to the tangent vector of the particular frame. A location of the intersection between the segment and the reference line can be based on a curvature value of the segment. Optimizing a candidate trajectory can include varying curvature values associated with various segments and determining costs of the various candidate trajectories.