Abstract: System, methods, and computer-readable media for a calibration check process of sensors on an autonomous vehicle (AV) via a drive-through environment mapped with a series of targets. The targets are used to check the calibration of the sensors on the AV as a quality check before the AV is determined fit to drive autonomously. Supervising a calibration process that collects data from the sensors on the AV based on exposure to a series of targets or augmented camera targets. The collected data may be used for extrinsic calibration aimed to determine that extrinsic parameters that define the rigid relationship between sensors are in set checker bounds.

Abstract: Technologies for managing a world model of a monitored area includes a roadway server configured to receive LIDAR sensing data from a LIDAR sensing system positioned to monitor the monitored area and generate a world map of the monitored area based on the LIDAR sensing data. The world model includes data that identifies objects located in the monitored area. The roadway server may distribute the world model to automated vehicles traveling through the monitored area via a stream or in response to directed requests. The roadway server may also receive sensor data from the automated vehicles, which may be used to generate the world model. The roadway server may distribute the world model to other interested devices located in or near the monitored area.

Abstract: According to one embodiment, an apparatus includes an interface to receive sensor data from a plurality of sensors of an autonomous vehicle. The apparatus also includes processing circuitry to apply a sensor abstraction process to the sensor data to produce abstracted scene data, and to use the abstracted scene data in a perception phase of a control process for the autonomous vehicle. The sensor abstraction process may include one or more of: applying a Sensor data response normalization process to the sensor data, applying a warp process to the sensor data, and applying a filtering process to the sensor data.

Abstract: An apparatus comprising at least one interface to receive sensor data from a plurality of sensors of a vehicle; and one or more processors to autonomously control driving of the vehicle according to a path plan based on the sensor data; determine that autonomous control of the vehicle should cease; send a handoff request to a remote computing system for the remote computing system to control driving of the vehicle remotely; receive driving instruction data from the remote computing system; and control driving of the vehicle based on instructions included in the driving instruction data.

Abstract: Sensor data is received from a plurality of sensors, where the plurality of sensors includes a first set of sensors and a second set of sensors, and at least a portion of the plurality of sensors are coupled to a vehicle. Control of the vehicle is automated based on at least a portion of the sensor data generated by the first set of sensors. Passenger attributes of one or more passengers within the autonomous vehicles are determined from sensor data generated by the second set of sensors. Attributes of the vehicle are modified based on the passenger attributes and the sensor data generated by the first set of sensors.

Abstract: Technologies for managing a world model of a monitored area includes a roadway server configured to receive LIDAR sensing data from a LIDAR sensing system positioned to monitor the monitored area and generate a world map of the monitored area based on the LIDAR sensing data. The world model includes data that identifies objects located in the monitored area. The roadway server may distribute the world model to automated vehicles traveling through the monitored area via a stream or in response to directed requests. The roadway server may also receive sensor data from the automated vehicles, which may be used to generate the world model. The roadway server may distribute the world model to other interested devices located in or near the monitored area.

Abstract: Gathering tenant usage data of server resources. A method includes a server in a cluster providing server resources for one or more tenants of the server. Data is stored in a local usage cache at the server. The data characterizes the resources provided to the one or more tenants of the server. At the server, data stored in the local usage cache is aggregated on a tenant basis, such that data is aggregated for given tenants. The aggregated data is sent to a distributed cache. At the server, aggregated data from other servers in the cluster is received from the distributed cache. The aggregated data from other servers in the cluster is globally aggregated and stored at an aggregated usage cache at the server in the globally aggregated form.

Abstract: Gathering tenant usage data of server resources. A method includes a server in a cluster providing server resources for one or more tenants of the server. Data is stored in a local usage cache at the server. The data characterizes the resources provided to the one or more tenants of the server. At the server, data stored in the local usage cache is aggregated on a tenant basis, such that data is aggregated for given tenants. The aggregated data is sent to a distributed cache. At the server, aggregated data from other servers in the cluster is received from the distributed cache. The aggregated data from other servers in the cluster is globally aggregated and stored at an aggregated usage cache at the server in the globally aggregated form.