Abstract: The present disclosure provides a vehicle positioning method, an apparatus and an autonomous driving vehicle, relating to autonomous driving in the technical field of artificial intelligence, which can be applied to high-definition positioning of the autonomous driving vehicle, the method including: if there is no high-definition map in a vehicle, acquiring intermediate pose information of the vehicle based on a global navigation satellite system and/or an inertial measurement unit in the vehicle, and determining the intermediate pose information as global positioning information; acquiring local positioning information; performing fusion processing to the global pose information and the local pose information to obtain fused pose information; performing compensation processing to the fused pose information according to the global attitude angle information and the local attitude angle information to obtain a position of the vehicle.

Abstract: A positioning method based on a lane line and a feature point, an electronic device, and a storage medium, which relate to fields of computer, automatic driving, intelligent transportation, computer vision. The method may include: determining first real-time measurement residuals according to first sensor information of a movable object detected, the first real-time measurement residuals including a first inertial measurement unit measurement residual, a first lane line measurement residual and a first non-lane line measurement residual; updating a state vector of the movable object according to a kinematic model of an inertial measurement unit and the first real-time measurement residuals; and determining a pose of the movable object at a time instant corresponding to the updated state vector according to a pose vector in the updated state vector.

Abstract: The present disclosure provides a vehicle positioning method, an apparatus and an autonomous driving vehicle, relating to autonomous driving in the technical field of artificial intelligence, which can be applied to high-definition positioning of the autonomous driving vehicle, the method including: if there is no high-definition map in a vehicle, acquiring intermediate pose information of the vehicle based on a global navigation satellite system and/or an inertial measurement unit in the vehicle, and determining the intermediate pose information as global positioning information; acquiring local positioning information; performing fusion processing to the global pose information and the local pose information to obtain fused pose information; performing compensation processing to the fused pose information according to the global attitude angle information and the local attitude angle information to obtain a position of the vehicle.

Abstract: The disclosed embodiments provide a system for forecasting container-based resource usage. During operation, the system obtains time-series data containing resource allocations for applications deployed in one or more containers within a set of hosts. Next, the system applies one or more machine learning models to the time-series data to estimate a growth rate associated with use of a resource by an application. The system then determines an increase in allocation of the resource to the application that supports the estimated growth rate. Finally, the system outputs the increase in allocation for use in managing use of resources within the set of hosts.

Abstract: The disclosed embodiments provide a system for forecasting container-based resource usage. During operation, the system obtains time-series data containing resource allocations for applications deployed in one or more containers within a set of hosts. Next, the system applies one or more machine learning models to the time-series data to estimate a growth rate associated with use of a resource by an application. The system then determines an increase in allocation of the resource to the application that supports the estimated growth rate. Finally, the system outputs the increase in allocation for use in managing use of resources within the set of hosts.