Abstract: The present disclosure provides a task migration method, apparatus, electronic device and storage medium, and relates to the technical field of data processing. The method may include: obtaining a task submitted by a user; in the case that the task is a Hadoop task and it is determined that task conversion is to be performed, converting Hadoop parameters in the task into parameters recognizable by a Spark; and injecting a conversion result into a predetermined kit and submitting the predetermined kit to a Spark cluster. The solution of the present disclosure may be applied to reduce the user's workload and enhance the processing efficiency etc.

Abstract: The present disclosure provides a vehicle positioning method implemented by an electronic device, including: obtaining sensor data about N frames of a vehicle through a sliding window, N being a positive integer; creating a target function for a factor graph model in accordance with the sensor data about the N frames, and performing optimization solution on the target function; and determining a pose and a position of the vehicle in accordance with a target value obtained through the optimization solution on the target function.

Abstract: The present disclosure provides a vehicle positioning method implemented by an electronic device, including: obtaining sensor data about N frames of a vehicle through a sliding window, N being a positive integer; creating a target function for a factor graph model in accordance with the sensor data about the N frames, and performing optimization solution on the target function; and determining a pose and a position of the vehicle in accordance with a target value obtained through the optimization solution on the target function.

Abstract: The present disclosure provides a task migration method, apparatus, electronic device and storage medium, and relates to the technical field of data processing. The method may include: obtaining a task submitted by a user; in the case that the task is a Hadoop task and it is determined that task conversion is to be performed, converting Hadoop parameters in the task into parameters recognizable by a Spark; and injecting a conversion result into a predetermined kit and submitting the predetermined kit to a Spark cluster. The solution of the present disclosure may be applied to reduce the user's workload and enhance the processing efficiency etc.

Abstract: The present disclosure provides a control method and apparatus for an autonomous vehicle, a computer device and a storage medium. The current steering wheel angle, vehicle speed and yaw rate are obtained, the current steering wheel angle is corrected based on the first correction deviation coefficient and the second correction deviation coefficient of the previous cycle, the corrected steering wheel angle and the current vehicle speed are input into the preset vehicle dynamic model to obtain the estimated yaw rate, the first yaw rate deviation value between the current yaw rate and the estimated yaw rate is obtained, and processed by the preset closed-loop algorithm to obtain the first correction deviation coefficient and the second correction deviation coefficient of the current cycle, and the target steering wheel angle is corrected, and the vehicle is driven based on the corrected target steering wheel angle.

Abstract: The present disclosure provides a method and an apparatus for determining positioning information of a vehicle, an electronic device, a storage medium and a computer program product, relating to the field of artificial intelligence, in particular to the field of intelligent driving. The method includes: receiving positioning results and error ranges of the positioning results from at least two positioning subsystems in a vehicle; determining reliability detection results of the positioning results of the positioning subsystems according to the error ranges of the positioning results; and determining positioning information of the vehicle according to a first positioning result of a positioning subsystem whose reliability detection result is “reliable”, and determining an error range of the positioning information, where the error range of the positioning information represents a confidence level of the positioning information.

Abstract: The present disclosure provides a control method and apparatus for an autonomous vehicle, a computer device and a storage medium. The current steering wheel angle, vehicle speed and yaw rate are obtained, the current steering wheel angle is corrected based on the first correction deviation coefficient and the second correction deviation coefficient of the previous cycle, the corrected steering wheel angle and the current vehicle speed are input into the preset vehicle dynamic model to obtain the estimated yaw rate, the first yaw rate deviation value between the current yaw rate and the estimated yaw rate is obtained, and processed by the preset closed-loop algorithm to obtain the first correction deviation coefficient and the second correction deviation coefficient of the current cycle, and the target steering wheel angle is corrected, and the vehicle is driven based on the corrected target steering wheel angle.