Abstract: A situational awareness system is described that comprises a processor and memory storing instructions executable by the processor. The instructions comprise to: determine at least one object of interest relative to a target vehicle; determine an assignment optimization at least one of a plurality of mobile devices to the at least one object of interest; and assign the at least one of the plurality of mobile devices to the at least one object of interest.

Abstract: A system comprises a computer including a processor, and a memory. The memory stores instructions such that the processor is programmed to determine two or more clusters of vehicle operating parameter values from each of a plurality of vehicles at a location within a time. Determining the two or more clusters includes clustering data from the plurality of vehicles based on proximity to two or more respective means. The processor is further programmed to determine a reportable condition when a mean for a cluster representing a greatest number of vehicles varies from a baseline by more than a threshold.

Abstract: A system includes a Lidar sensor and a processor. The processor is programmed to detect, using Lidar sensor data, a low-density area comprising a plurality of Lidar beam reflections less than a threshold, to determine dimensions of the area, and to determine that the area represents a physical object based on the detection and determination.

Abstract: A computer includes a processor and a memory. The memory stores instructions executable by the processor to receive, in a vehicle, object data from an external node, and upon identifying a point, in the received object data, that is within a volume defined based on vehicle position data received from a vehicle sensor, to determine an adjusted vehicle position based on the identified point and the vehicle position data.

Abstract: A system includes a light source configured to emit light in a wavelength in a visible range and a wavelength in an infrared range, and a vehicle including an infrared camera, and a computer programmed to identify an object based at least in part on an infrared image from the camera.

Abstract: A computing system receive first sensor data including moving objects and multi-modal LiDAR map data wherein the first sensor is calibrated based on a cost function that alternates between LiDAR map point cloud data and LiDAR map ground reflectivity data as input. The computing system can operate the vehicle based on the moving objects.

Abstract: A map of an area is generated from first sensor data of a first field of view including a blocked area and second sensor data of a second field of view having an unblocked view of the blocked area.

Abstract: A system, comprising a processor; and a memory, the memory including instructions to be executed by the processor to acquire a first image of a scene, acquire a second image of the scene while illuminating the scene, identify pixel blooming in a subtracted image determined by subtracting the first image from the second image, remediating the pixel blooming based on empirically determined parameters, and operate a vehicle based on the subtracted image.

Abstract: A map is received in a vehicle. The map is generated from infrastructure node sensor data specifying a location and a measurement of a physical value controlling vehicle operation at the location. A maneuver for the vehicle is determined based in part on the physical value and the location.

Abstract: A system includes a light source configured to emit light in a wavelength in a visible range and a wavelength in an infrared range, and a vehicle including an infrared camera, and a computer programmed to identify an object based at least in part on an infrared image from the camera.

Abstract: In a computer mounted to a stationary support structure a vehicle and an object proximate to the support structure can be detected from data from a sensor mounted to the support structure. A risk condition can be identified based on the detected vehicle and object.

Abstract: Data is received from a vehicle in a stationary support structure. One or more physical attributes of an infrastructure element is determined based on the vehicle data.

Abstract: A system, comprising a processor; and a memory, the memory including instructions to be executed by the processor to acquire a first image of a scene, acquire a second image of the scene while illuminating the scene, identify pixel blooming in a subtracted image determined by subtracting the first image from the second image, remediating the pixel blooming based on empirically determined parameters, and operate a vehicle based on the subtracted image.