Abstract: Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.

Abstract: Systems and methods for displaying imagery on a Light Detection and Ranging (LIDAR) system are provided. In one example embodiment, a method includes determining, by the one or more computing devices, a rotational frequency of a LIDAR device located on a vehicle. The method includes illuminating, by the one or more computing devices, one or more of a plurality of light emitting elements coupled to the LIDAR device based at least in part on the rotational frequency of the LIDAR device and the one or more images for display.

Abstract: Vehicle control systems can include one or more location sensors, an energy storage device, one or more charge sensors and one or more vehicle computing devices. The location sensor(s) can determine a current location of a vehicle, while the charge sensor(s) can determine a current state of charge of an energy storage device that can be located onboard the vehicle to provide operating power for one or more vehicle systems. The vehicle computing device(s) can communicate the current location of the vehicle and current state of charge of the energy storage device to a remote computing device, receive from the remote computing device a charging control signal determined, at least in part, from the current location of the vehicle and the current state of charge of the energy storage device, and control charging of the energy storage device in accordance with the charging control signal.

Abstract: Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.

Abstract: Vehicle control systems can include one or more location sensors, an energy storage device, one or more charge sensors and one or more vehicle computing devices. The location sensor(s) can determine a current location of a vehicle, while the charge sensor(s) can determine a current state of charge of an energy storage device that can be located onboard the vehicle to provide operating power for one or more vehicle systems. The vehicle computing device(s) can communicate the current location of the vehicle and current state of charge of the energy storage device to a remote computing device, receive from the remote computing device a charging control signal determined, at least in part, from the current location of the vehicle and the current state of charge of the energy storage device, and control charging of the energy storage device in accordance with the charging control signal.

Abstract: The present disclosure is directed to communicating autonomous-vehicle status. In particular, the methods, devices, and systems of the present disclosure can: determine one or more maintenance statuses of one or more of multiple different systems of an autonomous vehicle; and depict at least one of the status(es) via a display device affixed to an exterior of the autonomous vehicle and configured to display information associated with the multiple different systems such that the information is visible to an observer located outside the autonomous vehicle.

Abstract: Vehicle control systems can include one or more location sensors, an energy storage device, one or more charge sensors and one or more vehicle computing devices. The location sensor(s) can determine a current location of a vehicle, while the charge sensor(s) can determine a current state of charge of an energy storage device that can be located onboard the vehicle to provide operating power for one or more vehicle systems. The vehicle computing device(s) can communicate the current location of the vehicle and current state of charge of the energy storage device to a remote computing device, receive from the remote computing device a charging control signal determined, at least in part, from the current location of the vehicle and the current state of charge of the energy storage device, and control charging of the energy storage device in accordance with the charging control signal.

Abstract: A device for moving air comprising a piezoelectric element attached to a planar body. The planar body is configured to oscillate at a movable end generating an airflow in response to applying alternating electric current to said piezoelectric element. The device further comprises a partial cavity defined by a base plate, a first wall and a second wall which surrounds the movable end of the planar body. The base plate further comprises an opening located proximate to said movable end of the planar body. In operation the air flow generated by the planar body is forced out of the device through the opening.

Abstract: Disclosed herein are system, method, and computer program product embodiments providing a personalized interaction and navigation system. An embodiment operates by receiving, during a computing session, an indication of a first interaction with a currently accessed document stored in a computing system. It is determined that the first document is not included in the set of previously accessed documents. A new tab is added to the interface corresponding to the currently accessed document based upon the determining. The new tab is maintained on the interface for the duration of the computing session, wherein upon completion of the computing session, a determination is made whether to persist the tab beyond the computing session based on a request or to automatically remove the tab from the interface and the cache.

Abstract: Systems and methods are directed to matching an available vehicle to a rider requesting a service. In one example, a computer-implemented method includes obtaining, by a computing system comprising one or more computing devices, a service request from a rider. The method further includes obtaining, by the computing system, data indicative of a current location of the rider; and determining that the current location of the rider is within proximity of an autonomous vehicle queuing location. The method further includes providing, by the computing system, data to the rider to provide for selection of an available autonomous vehicle at the autonomous vehicle queuing location. The method further includes obtaining, by the computing system, rider authentication data upon a selection of an autonomous vehicle by the rider; and, in response to obtaining rider authentication data, matching an autonomous vehicle selected by the rider to provide for performance of the service request.

Abstract: Systems and methods for adjusting autonomous vehicle parameters in response to passenger feedback are provided. A method can include obtaining, by a computing system comprising one or more computing devices, passenger input data descriptive of one or more passenger experiences associated with one or more autonomous driving sessions, obtaining, by the computing system, one or more vehicle data logs descriptive of vehicle conditions associated with the passenger input data descriptive of one or more passenger experiences associated with the one or more autonomous driving sessions, determining, by the computing system using a machine-learned model, an adjusted vehicle parameter of an autonomous vehicle based at least in part on the passenger input data descriptive of one or more passenger experiences and the associated one or more vehicle data logs descriptive of vehicle conditions, and implementing, by the computing system, the adjusted vehicle parameter in an operation of the autonomous vehicle.

Abstract: Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining data indicative of a location associated with a user to which an autonomous vehicle is to travel. The autonomous vehicle is to travel along a first vehicle route that leads to the location. The method includes obtaining traffic data associated with a geographic area that includes the location. The method includes determining an estimated traffic impact of the autonomous vehicle on the geographic area based at least in part on the traffic data. The method includes determining vehicle action(s) based at least in part on the estimated traffic impact and causing the autonomous vehicle to perform the vehicle action(s) that include at least one of stopping the autonomous vehicle at least partially in a travel way within a vicinity of the location or travelling along a second vehicle route.

Abstract: Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.

Abstract: Systems and methods for displaying imagery on a Light Detection and Ranging (LIDAR) system are provided. In one example embodiment, a method includes determining, by the one or more computing devices, a rotational frequency of a LIDAR device located on a vehicle. The method includes illuminating, by the one or more computing devices, one or more of a plurality of light emitting elements coupled to the LIDAR device based at least in part on the rotational frequency of the LIDAR device and the one or more images for display.

Abstract: Vehicle control systems can include one or more location sensors, an energy storage device, one or more charge sensors and one or more vehicle computing devices. The location sensor(s) can determine a current location of a vehicle, while the charge sensor(s) can determine a current state of charge of an energy storage device that can be located onboard the vehicle to provide operating power for one or more vehicle systems. The vehicle computing device(s) can communicate the current location of the vehicle and current state of charge of the energy storage device to a remote computing device, receive from the remote computing device a charging control signal determined, at least in part, from the current location of the vehicle and the current state of charge of the energy storage device, and control charging of the energy storage device in accordance with the charging control signal.

Abstract: A system for communicating BPL signals is provided, including a BPL modem having a first internal modem and a second internal modem, the first internal modem and the second internal modem each in communication with a RF combiner; the RF combiner in communication with a medium voltage power line; and wherein the RF combiner combines signals from the first internal modem and the second internal modem into a single signal, and communicates the single signal to the medium voltage power line.

Abstract: Systems and methods for displaying imagery on a Light Detection and Ranging (LIDAR) system are provided. In one example embodiment, a method includes determining, by the one or more computing devices, a rotational frequency of a LIDAR device located on a vehicle. The method includes illuminating, by the one or more computing devices, one or more of a plurality of light emitting elements coupled to the LIDAR device based at least in part on the rotational frequency of the LIDAR device and the one or more images for display.

Abstract: A system for communicating BPL signals is provided, including a BPL modem having a first internal modem and a second internal modem, the first internal modem and the second internal modem each in communication with a RF combiner; the RF combiner in communication with a medium voltage power line; and wherein the RF combiner combines signals from the first internal modem and the second internal modem into a single signal, and communicates the single signal to the medium voltage power line.

Abstract: Use of spoken input for user devices, e.g. smartphones, can be challenging due to presence of other sound sources. Blind source separation (BSS) techniques aim to separate a sound generated by a particular source of interest from a mixture of different sounds. Various BSS techniques disclosed herein are based on recognition that providing additional information that is considered within iterations of a nonnegative tensor factorization (NTF) model improves accuracy and efficiency of source separation. Examples of such information include direction estimates or neural network models trained to recognize a particular sound of interest. Furthermore, identifying and processing incremental changes to an NTF model, rather than re-processing the entire model each time data changes, provides an efficient and fast manner for performing source separation on large sets of quickly changing data. Carrying out at least parts of BSS techniques in a cloud allows flexible utilization of local and remote sources.