Abstract: An audio notification system for an autonomous vehicle (AV) determines that the AV is within range of a user and emits a sound though a speaker of the AV to notify that the user that the vehicle has arrived. The audio notification system may include a sensor for sensing that the user has accessed the AV, and turns off the sound in response to the user accessing the AV. The audio notification may be generated according to one or more audio options, e.g., volume, pitch, or audio pattern.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination and selecting one of a plurality of possible routes between the origin and the destination. For each of a plurality of route segments of the selected route, mapping information is used to characterize the route segment and one of a plurality of driving modes is selected for the route segment based on the characterization of the route segment and the at least one of the item characteristic and the item identity. A driving plan comprising a collection of the selected driving modes corresponding to the plurality of route segments comprising the selected route is provided to a vehicle and the vehicle delivers the item from the origin to the destination via the selected route using the driving plan.

Abstract: An audio notification system for an autonomous vehicle (AV) determines that the AV is within range of a user and emits a sound though a speaker of the AV to notify that the user that the vehicle has arrived. The audio notification system may include a sensor for sensing that the user has accessed the AV, and turns off the sound in response to the user accessing the AV. The audio notification may be generated according to one or more audio options, e.g., volume, pitch, or audio pattern.

Abstract: Systems and methods are provided for monitoring deliveries in an autonomous vehicle. In particular, systems and methods are provided for monitoring the conditions of the interior of a delivery container inside an autonomous vehicle. In various implementations, the delivery container includes one or more compartments, and the conditions of each of the one or more compartments is monitored.

Abstract: There is disclosed herein examples of a vehicle container unit that may be mounted within a vehicle. The vehicle container unit may be mounted to a seat of a vehicle and may include space for transporting items within the vehicle container unit. The vehicle container unit may mount to the seat via an anchor system of the seat.

Abstract: The present disclosure provides a method comprising detecting an event in connection with an autonomous vehicle, wherein the detected event comprises at least one of a current state of the autonomous vehicle, an impending state of the autonomous vehicle, and an intent of the autonomous vehicle; generating an image in connection with the detected event, wherein the image comprises at least one of text information and graphics information; and displaying the generated image on at least one window of the autonomous vehicle for conveying information about the detected event to at least one user located outside the autonomous vehicle.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination; identifying a plurality of possible routes between the origin and the destination using mapping information, the mapping information including for each of the plurality of possible routes, a characterization of each of a plurality of route segments comprising the possible route; evaluating the plurality of possible routes in view of the identified at least one of the item characteristic and the item identity to select one of the plurality of possible routes; and providing the selected one of the plurality of possible routes to a vehicle, wherein the vehicle delivers the item from the origin to the destination via the identified route.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination; identifying a plurality of possible routes between the origin and the destination using mapping information, the mapping information including for each of the plurality of possible routes, a characterization of each of a plurality of route segments comprising the possible route; evaluating the plurality of possible routes in view of the identified at least one of the item characteristic and the item identity to select one of the plurality of possible routes; and providing the selected one of the plurality of possible routes to a vehicle, wherein the vehicle delivers the item from the origin to the destination via the identified route.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination; identifying a plurality of possible routes between the origin and the destination using mapping information, the mapping information including for each of the plurality of possible routes, a characterization of each of a plurality of route segments comprising the possible route; evaluating the plurality of possible routes in view of the identified at least one of the item characteristic and the item identity to select one of the plurality of possible routes; and providing the selected one of the plurality of possible routes to a vehicle, wherein the vehicle delivers the item from the origin to the destination via the identified route.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: An audio notification system for an autonomous vehicle (AV) determines that the AV is within range of a user and emits a sound though a speaker of the AV to notify that the user that the vehicle has arrived. The audio notification system may include a sensor for sensing that the user has accessed the AV, and turns off the sound in response to the user accessing the AV. The audio notification may be generated according to one or more audio options, e.g., volume, pitch, or audio pattern.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Systems and methods of leveraging machine learning to predict user generated content are provided. For instance, first entity data associated with an entity can be received. The first entity data can include user specified data associated with an attribute of the entity. The first entity data can be input into a machine-learned content prediction model. Inferred entity data can be received as output of the machine-learned content prediction model. The inferred entity data can include inferred data descriptive of the attribute of the entity.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Methods and system are disclosed that manage behavior of a graphical user interface associated with an application during a runtime of the application. In one aspect, the graphical user interface (GUI) may be configured with attributes associated with the application by a GUI configuration manager. Upon determining application configuration information, a data field metadata manager may determine data fields to be mapped onto the GUI. The data field metadata manager may read the metadata information associated with the data fields that may include data field attributes and domain values. A GUI metadata manager may retrieve metadata information associated with the mapped data fields. A GUI runtime manager may manage the behavior of the GUI and the data received by the data fields may be saved in a data store in a data format associated with the application.

Abstract: Systems and methods of leveraging machine learning to predict user generated content are provided. For instance, first entity data associated with an entity can be received. The first entity data can include user specified data associated with an attribute of the entity. The first entity data can be input into a machine-learned content prediction model. Inferred entity data can be received as output of the machine-learned content prediction model. The inferred entity data can include inferred data descriptive of the attribute of the entity.