Vehicle computing resource using method based on trajectory prediction

Abstract

In order to solve the problem in the prior art that the limited computing resources provided by a near-end edge server cannot adapt to the increased number of vehicles, the present invention provides a vehicle computing resource using method based on trajectory prediction. The method comprises the steps of: when a task-requesting vehicle has a computing task requirement, firstly predicting, according to the historical driving trajectory of the vehicle, whether the future driving trajectories of surrounding vehicles are similar to the future driving trajectory of a task-issuing vehicle; then, selecting out and classifying the vehicles having similar future driving trajectories to the task-issuing vehicle; then, determining the vehicles to participate in the tasks and creating a corresponding contract for the vehicle; finally, after the contract with maximized benefit of the task-requesting vehicle is obtained, uploading, by the task-requesting vehicle, all tasks to the task-executing vehicles successively, and enabling the task-executing vehicles to successively process the tasks and successively return task processing results to the task-requesting vehicle after processing the task to end the tasks.

Description

technical field [0001] The invention relates to the field of resource utilization in the Internet of Vehicles technology, in particular to a method for utilizing vehicle computing resources based on trajectory prediction. Background technique [0002] The Internet of Vehicles (IOV), as a promising application domain of the Internet of Things (IOT), has attracted extensive attention from both industry and academia. IOV has become a research field for the development of industrial applications in smart cities, and the key research contents include: traffic management and road safety. Many countries are focusing on establishing IOV systems, such as ERTICO-ITS in Europe. In the industrial field, global automakers such as Volvo and BMW have developed test bench systems based on vehicle-to-vehicle (V2V) communication. [0003] In 2018, the global vehicle population has reached 1.34 billion, and it is expected to reach 2 billion by 2035. Future vehicle services will inevitably r...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem in the prior art that the computing resources provided by the near-end edge server are limited and unable to adapt to the exponentially increasing number of vehicles, the present invention provides a method for utilizing vehicle computing resources based on trajectory prediction

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