Uber Technologies, Inc.

Uatc, LLC

The Heil Co.

Rowbot Systems LLC

John Evan Bares

Matthew Sweeney

William Payne Ross

David LaRose

Brian T Parker

Thomas L Price

Robert H Doll

Chenggang Liu

Kent Cavender-Bares

Matthew Camacho-Cook

A transport arrangement system operates to receive a transport request from a user, and to make a selection of a vehicle type for the user based at least in part on a set of criteria associated with the transport request or user information. For example, the determination of whether an autonomous vehicle is to be provided can be based at least in part on the destination specified with the transport request.

Selecting vehicle type for providing transport

A refuse collection vehicle has a container collection arm with a telescoping boom coupled with a refuse stowage unit of the vehicle. A grasping mechanism is coupled with an end of the boom. A rotary actuator couples the grasping mechanism with the boom to enable a waste container to be moved between a pick up position and a dump position.

Refuse collection vehicle with telescoping arm

Sensor information is collected from human driven vehicles which are driven in a given region. From the sensor information, a road condition is detected on a road segment, where the road condition has a sufficiently high likelihood of impairing autonomous vehicles in safely navigating through the one or more road segments. Information about the one or more road segments is communicated to the one or more autonomous vehicles.

Autonomous vehicle operated with guide assistance of human driven vehicles

The present disclosure provides systems and methods for automatic event detection and classification for autonomous vehicles. One example method includes obtaining, by one or more computing devices, vehicle data descriptive of vehicle conditions associated with an autonomous vehicle during an autonomous driving session. The method includes extracting, by the one or more computing devices, a plurality of features from the vehicle data. The method includes determining, by the one or more computing devices using a machine-learned classifier, a classification for each of one or more candidate events based at least in part on one or more of the plurality of features that are respectively associated with the one or more candidate events. The method includes associating, by the one or more computing devices, the classification determined for each of the one or more candidate events with the vehicle data.

Machine learning for event detection and classification in autonomous vehicles

An event is detected that impairs a confidence level of the autonomous vehicle in progressing through a current route. In response to detecting the event, the autonomous vehicle communicates information about the event to a remote source of guidance. The autonomous vehicle can receive instructions from the remote source of guidance on how to handle the event. The autonomous vehicle can then implement the instructions to handle the event while it operates.

Providing remote assistance to an autonomous vehicle

Examples described herein include an autonomous vehicle that receives guide assistance from a human driven vehicle in response to a determination that the autonomous vehicle cannot progress safely on its route.

An autonomous vehicle platform and system for selectively performing an in-season management task in an agricultural field while self-navigating between rows of planted crops, the autonomous vehicle platform having a vehicle base with a width so dimensioned as to be insertable through the space between two rows of planted crops, the vehicle base having a first portion and a second portion, wherein the first portion is pivotably coupled to the second portion, and each of portion is operably coupled to at least one ground engaging wheel.

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Gibsonia, PA, United States of America

John Evan Bares