Gm Global Technolgoy Operations, Inc.

Gm Cruise Holdings LLC

Drew Gross

Ian Rust

Solomon Bier

Brian Pierce

Gillian Langor

Kyle Vogt

Shiva Ghose

Haven Lau

Matthias Wisniowski

Kevin Chu

Eric Lujan

Sohrab Haghighat

Brooks Reed

Benjamin Earle Weinstein-Raun

John Hoare

Daniel Loman

Serhiy Buslovskyy

Ryan Kollar

Andreas Pasternak

Florian Courbet

Kais Sorrels

Sneha Sinha

Jonathan Lenoff

Disclosed are embodiments for facilitating restarting operations for recovery processes in autonomous systems. In some aspects, an embodiment includes determining that an autonomous vehicle (AV) is experiencing a failure condition; identifying a plurality of restart operations to apply to one or more components of the AV contributing to the failure condition; prior to applying a restart operation of the plurality of restart operations, determining that safety conditions corresponding to the restart operation are satisfied; and applying the plurality of restart operations to the AV in accordance with an increasing order of disruptiveness of each of the restart operations to operations of the AV.

Restarting operations for recovery processes in autonomous systems

Micro-authorization of remote assistance for an autonomous vehicle is described herein. A constraint that inhibits propulsion by a mechanical system of the autonomous vehicle is activated by a computing system of the autonomous vehicle, wherein a signal that identifies the activated constraint is transmitted from the autonomous vehicle to a remote computing system. The remote computing system generates instructions to deactivate the activated constraint. A return signal is transmitted from the remote computing system that specifies instructions to deactivate the constraint and a distance to desirably advance the autonomous vehicle. The computing system of the autonomous vehicle deactivates the constraint and the mechanical system is controlled to advance the autonomous vehicle when signal latency is less than a predetermined threshold duration of time.

Micro-authorization of remote assistance for an autonomous vehicle

An autonomous vehicle configured to perform a lane change maneuver is described herein. The autonomous vehicle includes several different types of sensor systems, such as image, lidar, radar, sonar, infrared, and GPS. The autonomous vehicle additionally includes a computing system that executes instructions on a lane change detection system and a control system. The lane change detection system includes a region of interest module and an object trajectory module for determining whether the autonomous vehicle will collide with another object if the autonomous vehicle maneuvers into an adjacent lane. An instruction module of the lane change detection system is further used to facilitate operational control of a mechanical system of the autonomous vehicle, such as an engine or a steering system.

Lane change detection system and method for an autonomous vehicle

Systems and method are provided for controlling a vehicle. In various embodiments, a method of path planning for a vehicle includes receiving sensor data relating to an environment associated with the vehicle; defining a region of interest for the vehicle, based on the sensor data; defining a graph comprising a plurality of nodes, each of the plurality of nodes comprising a state of the vehicle and an associated cost, based on a cost function as applied to the state of the vehicle, at one of a plurality of points in time; and performing, via a processor, a search of the graph, based on the associated costs of each node of the graph, to determine a selected path for the vehicle through the region of interest that minimizes a total cost via the graph.

Systems and methods for unprotected maneuver mitigation in autonomous vehicles

Systems and method are provided for controlling a vehicle. In one embodiment, a method includes calculating, via a router of a vehicle system that accesses road map data, at least one route to a destination based on the road map data, thereby producing route solution data. The vehicle system enters a remote assistance mode in response to remote assistance decision data received from a blockage arbiter of the vehicle system. In the remote assistance mode, the method includes determining, via the router, at least one road segment of the road map data that is permitted to be blacklisted, thereby producing permitted blacklist data. The method includes transmitting the permitted blacklist data and the route solution data, via a vehicle communications module of the vehicle system, to a remote vehicle assistance system. The method includes updating, via the router, the road map data to exclude at least one blacklisted road segment defined by the permitted blacklist data.

Vehicle remote assistance mode

Systems and methods are provided for remotely assisting an autonomous vehicle. The method includes: aggregating sensor data from the autonomous vehicle; identifying an assistance-desired scenario; generating an assistance request based on the sensor data; transmitting the assistance request to a remote assistance interface; and receiving and processing a response to the assistance request. The remote assistance interface includes a remote assistance interface that is used in generating the response to the assistance request.

System and method for remotely assisting autonomous vehicle operation

A method for controlling an autonomous vehicle using an external interface is disclosed. The method includes an external interface that is in operable communication with one or more control systems of the autonomous vehicle. The method allows an entity in proximity of an outside of the autonomous vehicle to interact with the external interface; receives from the entity one or more control inputs, and controls one or more operations of the autonomous vehicle based on the one or more control inputs.

System and method for externally interfacing with an autonomous vehicle

A system and method for providing routing instructions to one or more autonomous vehicles includes identifying a destination of an autonomous vehicle; identifying a starting position or an initial location of the autonomous vehicle; receiving autonomous vehicle sensor data; receiving one or more routing goals for a routing plan for the autonomous vehicle; generating one or more route modification parameters; and generating a route plan for the autonomous vehicle based on (a) the destination, (b) the starting position or the initial location, (c) the one or more route modification parameters and (d) the one or more routing goals.

System and method for autonomous vehicle fleet routing

Growing community of inventors

San Francisco, CA, United States of America

Drew Gross