Vehicle control method, device and equipment and computer storage medium

Abstract

The invention discloses a vehicle control method, device and equipment and a computer storage medium. The vehicle control method comprises the steps of obtaining a predicted acceleration sequence of a vehicle in a preset time period, determining a first transition probability matrix of the predicted acceleration sequence according to a preset driver model, calculating a difference value between the first transition probability matrix and the historical acceleration sequence data set according to a preset induction matrix norm, and when the difference value is smaller than a preset threshold value, determining an energy consumption strategy according to the first transition probability matrix, a preset energy constraint function and a preset reinforcement learning algorithm. According to the embodiment of the invention, reliable decisions, path plans and fuel consumption constraints of the vehicle can be generated based on the predicted acceleration sequence, so that the vehicle is controlled to run stably, and the energy consumption of the vehicle is reduced.

Description

technical field [0001] The invention belongs to the field of automatic driving, and in particular relates to a vehicle control method, device, equipment and computer storage medium. Background technique [0002] With more and more vehicles on the road, the road transport system is getting busier. To make transportation and mobility more intelligent and efficient, autonomous vehicles are considered as a promising solution. With remarkable achievements in external sensing, motion planning, and vehicle control, independent innovations in self-driving cars can well help the vehicle operate independently in pre-set scenarios. [0003] Usually, the system architecture in an autonomous vehicle is mainly composed of three processing modules: perception and localization module, motion planning module and trajectory controller module. Among them, the decision-making and path planning generated by the motion planning module are not only the key to control the safe and comfortable ope...

AI Technical Summary

Problems solved by technology

[0004] At present, the generated decision-making and path planning need to be combined with the acceleration sequence for a period of time in the future. When the predicted acceleration sequence does not exist in the historical acceleration sequence database, effective and reliable decision-making and path planning cannot be generated, resulting in unstable vehicle operation.

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