Hybrid vehicle queue distributed model prediction and control method

Abstract

The invention discloses a hybrid vehicle queue distributed model prediction and control method. The method comprises the following steps of firstly, dividing a hybrid vehicle queue into a plurality of mutually associated local hybrid vehicle queues; then establishing a model of each local hybrid queue based on a car-following model of networked automatic driving vehicles and human-drive vehicles; secondly, based on the local hybrid queue model, according to a model prediction control algorithm, establishing an overall control problem of the hybrid vehicle queue; and finally, in combination with an alternating direction multiplier method, constructing a distributed model prediction controller for each local hybrid queue to realize the overall formation control of the hybrid vehicle queue. The effectiveness of the method provided by the invention is verified by performing an experiment on an MATLAB simulation platform. Experimental results show that the method can ensure that the networked automatic driving vehicles and the human-driven vehicles in the hybrid vehicle queue achieve a good formation effect, and the networked automatic driving vehicles can be driven in a formation manner at a smaller inter-vehicle distance, so that the traffic capacity is effectively improved.

Description

technical field [0001] The invention relates to the field of automatic driving, the field of mixed vehicle platooning, and the field of Internet of Vehicles, in particular to a distributed model predictive control method for mixed vehicle platooning based on an alternating direction multiplier method. It is used to realize the formation control of mixed vehicle platoons including human-driven vehicles and networked autonomous vehicles, improve traffic capacity and reduce resource consumption. Background technique [0002] With the development of autonomous driving technology, network-connected autonomous vehicles driving in formation on highways has attracted extensive attention from researchers. Multi-vehicle cooperative formation control provides a new solution and approach to ensure travel safety, increase traffic capacity and reduce fuel consumption. Vehicle platooning aims to ensure that all vehicles in the same group travel at a common speed while maintaining a desire...

AI Technical Summary

Problems solved by technology

Although the above-mentioned distributed model predictive controllers have achieved certain results in improving the traffic flow formation control effect and improving road safety, they are designed using part of the vehicle information in the vehicle platoon, rather than from the overall vehicle platoon. Design from Control Targets

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