Waymo LLC

Earthlink, Inc.

David Smith

Craig Latimer

Joshua P Switkes

Andrew Barton-Sweeney

Diomidis Katzourakis

Christopher Bowen

Vadim Butakov

Eric Kim

Kevin Yoon

Fabrice Chupin

Scott Jarol

David Redkey

Aspects and implementations of the present disclosure address shortcomings of the existing technology by enabling routing of an autonomous vehicles (AV) by identifying routes from a first location to a second location, identifying a target efficiency value of autonomous driving along a respective route, determining, in view of historical data for the respective route and using one or more randomized conditions, a confidence level associated with the target efficiency value, selecting, based on the target efficiency values and the associated confidence level, a preferred route, and causing the AV to select the first route for travel from the first location to the second location.

Route optimization for autonomous driving systems

The technology relates to articulated autonomous vehicles that can potentially jackknife. To avoid or mitigate such hazardous conditions, the current state of the vehicle is evaluated against the vehicle's planned trajectory, for instance as it drives along a freeway or surface streets. When the evaluation indicates a likelihood of jackknifing, an automated braking approach is implemented using elective braking to stabilize the vehicle. The braking approach can depend on whether the situation involves tractor jackknifing or trailer jackknifing, and one or more different braking mechanisms can be employed for a selective modulation of the braking profile to address actual jackknifing or to prevent the vehicle from entering a jackknifing situation.

Systems and methods to address jackknifing in autonomous vehicles

A method includes identifying map data comprising driving constraint data for a route of an autonomous vehicle (AV), the map data being of a road network associated with the route of the AV, the driving constraint data being based on physical vehicle data. The method further includes, while the AV is travelling the route, identifying current environmental sensing data for a portion of the route. The method further includes causing, based on the map data comprising the driving constraint data for the route and the current environmental sensing data associated with the portion of the route, the AV to travel the portion of the route.

Physics-informed optimization for autonomous driving systems

A method includes identifying mass distribution data of an autonomous vehicle (AV). The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes determining, based on the mass distribution data, one or more handling maneuver limits for the AV. The method further includes causing the AV to travel a route based on the one or more handling maneuver limits.

Handling maneuver limits for autonomous driving systems

A method includes identifying sensor data associated with corresponding distal ends of one or more axles of an autonomous vehicle (AV). The method further includes determining, based on the sensor data, mass distribution data of the AV. The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes causing, based on the mass distribution data, performance of a corrective action associated with the AV.

Mass distribution-informed optimization for autonomous driving systems

A vehicle operable to pull a trailer comprising a payload is provided, that includes a plurality of sensors configured to capture sensor data related to the vehicle, the trailer, or both, and a controller configured to (i) receive the sensor data from the plurality of sensors, (ii) determine, based on the sensor data, one or more parameters associated with the trailer, the payload, or both, (iii) update, based on an analysis of the one or more parameters, a confidence level associated with an operation of the vehicle with the trailer and the payload, and (iv) based on the confidence level, responsively execute an autonomous control strategy comprising one or more adjustments to the operation of the vehicle.

Automatic qualification of payload for autonomous vehicles

A control command is provided to a vehicle control module that identifies one or more vehicle actions to be performed by the vehicle control module to control a position of an autonomous vehicle (AV) with respect to an external environment. Whether one or more conditions pertaining to the position of the AV with respect to the external environment are satisfied is determined. Responsive to determining that the one or more conditions pertaining to the position of the AV with respect to the external environment are satisfied, a first instruction is provide to the vehicle control module that permits the vehicle control module to deviate from the one or more vehicle actions identified in the control command and to perform an energy saving action with respect to the AV.

Energy saving actions for autonomous driving systems

A web browser for Internet access distinguishes between client users and supervisory users. Supervisory users are authorized to create or modify local content access settings to Internet resources that are stored in data structures. Client users are prevented from accessing these local content access settings. When a client user logs on, the local content access settings are retrieved from a local data structure and additional content access control information is retrieved from a remote data structure. Modules coordinate local and remote content access settings to regulate client access to Internet resources. Client access is readily modified through the setting of local content access settings by a local supervisor and by the selection of the remote site(s) contacted for additional content access control information. An interactive agent assists client users during Internet access.

Growing community of inventors

Cupertino, CA, United States of America

David Smith