Abstract: Apparatus and methods for extraction and calculation of multi-person performance metrics in a three-dimensional space. An example apparatus includes a detector to identify a first subject in a first image captured by a first image capture device based on a first set of two-dimensional kinematic keypoints in the first image, the two-dimensional kinematic keypoints corresponding to a joint of the first subject, the first image capture device associated with a first view of the first subject, a multi-view associator to verify the first subject using the first image and a second image captured by a second image capture device, the second image capture device associated with a second view of the first subject, the second view different than the first view, and a keypoint generator to generate three-dimensional keypoints for the first subject using the first set of two-dimensional kinematic keypoints.

Abstract: Techniques are disclosed for task priority scheduling and resource allocation of autonomous agents. The scheduling may utilize sensor data characteristics to facilitate scheduling decisions. The present disclosure also provides refinement of task priority scheduling utilizing fleet management information-based scene and environment information, such as by using information available to the fleet management controller.

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 intelligent traffic optimization include a directional flow server that receives dynamic traffic data from traffic infrastructure devices in a monitored region. The traffic data may include traffic volume data and traffic control status data. The server updates a dynamic layer of a high-definition map based on the dynamic traffic data. The high-definition map also includes a static layer and a directional flow layer. The server optimizes the directional flow in response to updating the dynamic layer. The directional flow layer is indicative of traffic direction associated with roads in the monitored region. The server may optimize each of several sub-regions and then optimize connection roads between the regions. The server may distribute the optimized directional flow layer to consumers such as traffic control devices, autonomous vehicles, and other subscribing devices. Other embodiments are described and claimed.

Abstract: Techniques are disclosed herein for collecting annotation data via a gamified user interface in a vehicle control system. According to an embodiment disclosed herein, the vehicle control system detects a trigger to initiate an annotation prompt associated with an object classified from an image. The vehicle control system presents, via a user interface, the annotation prompt. The vehicle control system receives, via the user interface, user input indicative of a response to the annotation prompt by a user and updates a confidence score associated with the classified object as a function of one or more metrics associated with the user.

Abstract: Apparatus and methods for extraction and calculation of multi-person performance metrics in a three-dimensional space. An example apparatus includes a detector to identify a first subject in a first image captured by a first image capture device based on a first set of two-dimensional kinematic keypoints in the first image, the two-dimensional kinematic keypoints corresponding to a joint of the first subject, the first image capture device associated with a first view of the first subject, a multi-view associator to verify the first subject using the first image and a second image captured by a second image capture device, the second image capture device associated with a second view of the first subject, the second view different than the first view, and a keypoint generator to generate three-dimensional keypoints for the first subject using the first set of two-dimensional kinematic keypoints.

Abstract: Technologies for intelligent traffic optimization include a directional flow server that receives dynamic traffic data from traffic infrastructure devices in a monitored region. The traffic data may include traffic volume data and traffic control status data. The server updates a dynamic layer of a high-definition map based on the dynamic traffic data. The high-definition map also includes a static layer and a directional flow layer. The server optimizes the directional flow in response to updating the dynamic layer. The directional flow layer is indicative of traffic direction associated with roads in the monitored region. The server may optimize each of several sub-regions and then optimize connection roads between the regions. The server may distribute the optimized directional flow layer to consumers such as traffic control devices, autonomous vehicles, and other subscribing devices. Other embodiments are described and claimed.

Abstract: Techniques are disclosed herein for collecting annotation data via a gamified user interface in a vehicle control system. According to an embodiment disclosed herein, the vehicle control system detects a trigger to initiate an annotation prompt associated with an object classified from an image. The vehicle control system presents, via a user interface, the annotation prompt. The vehicle control system receives, via the user interface, user input indicative of a response to the annotation prompt by a user and updates a confidence score associated with the classified object as a function of one or more metrics associated with the user.