Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining, from an autonomy system, data indicative of a planned trajectory of the autonomous vehicle through a surrounding environment. The method includes determining a region of interest in the surrounding environment based at least in part on the planned trajectory. The method includes controlling one or more first sensors to obtain data indicative of the region of interest. The method includes identifying one or more objects in the region of interest, based at least in part on the data obtained by the one or more first sensors. The method includes controlling the autonomous vehicle based at least in part on the one or more objects identified in the region of interest.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining, from an autonomy system, data indicative of a planned trajectory of the autonomous vehicle through a surrounding environment. The method includes determining a region of interest in the surrounding environment based at least in part on the planned trajectory. The method includes controlling one or more first sensors to obtain data indicative of the region of interest. The method includes identifying one or more objects in the region of interest, based at least in part on the data obtained by the one or more first sensors. The method includes controlling the autonomous vehicle based at least in part on the one or more objects identified in the region of interest.

Abstract: A computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location and manage the dynamic queue by routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs by transmitting updated navigation-related data to one or more of the matched transport providers.

Abstract: A computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location and manage the dynamic queue by routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs by transmitting updated navigation-related data to one or more of the matched transport providers.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Abstract: Systems and methods are provided for remotely detecting a status associated with an autonomous vehicle and generating control actions in response to such detections. In one example, a computing system can access a third-party communication associated with an autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a predetermined identifier associated with the autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a status associated with the autonomous vehicle, and transmit one or more control messages to the autonomous vehicle based at least in part on the predetermined identifier and the status associated with the autonomous vehicle.

Abstract: Systems and methods are provided for remotely detecting a status associated with an autonomous vehicle and generating control actions in response to such detections. In one example, a computing system can access a third-party communication associated with an autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a predetermined identifier associated with the autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a status associated with the autonomous vehicle, and transmit one or more control messages to the autonomous vehicle based at least in part on the predetermined identifier and the status associated with the autonomous vehicle.

Abstract: A transport facilitation system can receive a pick-up request from a computing device of a user of a transportation arrangement service, the pick-up request comprising a unique identifier and a pick-up location. Using the unique identifier, the system can perform a lookup in a database for a profile indicating vehicle setup preferences for the user, and select a service vehicle to service the pick-up request. The system can further determine a seat assignment within the service vehicle for the user, and based on the vehicle setup preferences indicated in the profile, the system transmit a set of configuration instructions to the service vehicle, the set of configuration instructions to configure one or more adjustable components of the service vehicle for the user.

Abstract: The present disclosure provides systems and methods that enable human supervision of a highly capable automated driving system. In particular, the systems and methods of the present disclosure enable a human (e.g., a passenger, driver/operator, or remote supervisor of an autonomous vehicle) to easily and quickly transition control of the autonomous vehicle from a primary motion plan that controls the vehicle towards a primary destination to a secondary motion plan that controls the vehicle to a safe state. As such, the systems and methods of the present disclosure enable advanced human supervision of autonomous vehicle behavior in which a human can cause an autonomous vehicle to operate in a risk-reduced manner or otherwise maneuver to a safe state, without requiring the human to actually assume manual control of the vehicle.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining, from an autonomy system, data indicative of a planned trajectory of the autonomous vehicle through a surrounding environment. The method includes determining a region of interest in the surrounding environment based at least in part on the planned trajectory. The method includes controlling one or more first sensors to obtain data indicative of the region of interest. The method includes identifying one or more objects in the region of interest, based at least in part on the data obtained by the one or more first sensors. The method includes controlling the autonomous vehicle based at least in part on the one or more objects identified in the region of interest.

Abstract: An autonomous vehicle is operable to follow a primary trajectory that forms a portion of a route. While controlling the autonomous vehicle, the autonomous vehicle calculates a failsafe trajectory to follow as a response to a predetermined type of event.

Abstract: A computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location and manage the dynamic queue by routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs by transmitting updated navigation-related data to one or more of the matched transport providers.

Abstract: A network computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or the transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location, and manage the dynamic queue by sequentially routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining, from an autonomy system, data indicative of a planned trajectory of the autonomous vehicle through a surrounding environment. The method includes determining a region of interest in the surrounding environment based at least in part on the planned trajectory. The method includes controlling one or more first sensors to obtain data indicative of the region of interest. The method includes identifying one or more objects in the region of interest, based at least in part on the data obtained by the one or more first sensors. The method includes controlling the autonomous vehicle based at least in part on the one or more objects identified in the region of interest.

Abstract: The present disclosure provides systems and methods that enable human supervision of a highly capable automated driving system. In particular, the systems and methods of the present disclosure enable a human (e.g., a passenger, driver/operator, or remote supervisor of an autonomous vehicle) to easily and quickly transition control of the autonomous vehicle from a primary motion plan that controls the vehicle towards a primary destination to a secondary motion plan that controls the vehicle to a safe state. As such, the systems and methods of the present disclosure enable advanced human supervision of autonomous vehicle behavior in which a human can cause an autonomous vehicle to operate in a risk-reduced manner or otherwise maneuver to a safe state, without requiring the human to actually assume manual control of the vehicle.

Abstract: An autonomous vehicle is operable to follow a primary trajectory that forms a portion of a route. While controlling the autonomous vehicle, the autonomous vehicle calculates a failsafe trajectory to follow as a response to a predetermined type of event.

Abstract: The present disclosure provides systems and methods that enable human supervision of a highly capable automated driving system. In particular, the systems and methods of the present disclosure enable a human (e.g., a passenger, driver/operator, or remote supervisor of an autonomous vehicle) to easily and quickly transition control of the autonomous vehicle from a primary motion plan that controls the vehicle towards a primary destination to a secondary motion plan that controls the vehicle to a safe state. As such, the systems and methods of the present disclosure enable advanced human supervision of autonomous vehicle behavior in which a human can cause an autonomous vehicle to operate in a risk-reduced manner or otherwise maneuver to a safe state, without requiring the human to actually assume manual control of the vehicle.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Abstract: A transport facilitation system can receive a pick-up request from a computing device of a user of a transportation arrangement service, the pick-up request comprising a unique identifier and a pick-up location. Using the unique identifier, the system can perform a lookup in a database for a profile indicating vehicle setup preferences for the user, and select a service vehicle to service the pick-up request. The system can further determine a seat assignment within the service vehicle for the user, and based on the vehicle setup preferences indicated in the profile, the system transmit a set of configuration instructions to the service vehicle, the set of configuration instructions to configure one or more adjustable components of the service vehicle for the user.