Intelligent Vehicle Cooperative Control Based On Distributed Model Predictive Control

With the sustained and rapid development of China's economy,the number of motor vehicles continues to grow at high rate.The increasing vehicles have brought serious traffic congestion,traffic accidents and environmental pollution to China's cities.In order to solve the above social problems,the Intelligent Transportation System(ITS)came into being,and the intelligent connected vehicle(ICV),which is an important part of the ITS,can achieve coorperative control through advanced in-vehicle sensors and V2X(Vehicle to Everyting)communication technology.The cooperative control between ICVs can effectively alleviate traffic congestion and environmental pollution,and reduce traffic accidents.The V2X-based cooperative control of ICVs is a hot research topic,and it includes vehicle coorperative formation control and vehicle cooperative optimization control.The vehicle cooperative optimization control is in the initial stage and has some deficiencies.Due to the important role of vehicle cooperative optimization control in solving the above social problems,to make up for the deficiencies of the vehicle cooperative optimization control,this paper focuses on vehicle cooperative optimization control,and conducts in-depth research on how to coordinate the realization of multiple platoon control objectives such as vehicle safety,passenger comfort and fuel economy.The specific research contents and innovations include the following aspects:1)For intelligent vehicle platoon(IVP)driving on a flat road,a vehicle cooperative switching control strategy that can achieve multiple platoon control objectives is proposed.The vehicle cooperative switching control strategy includes a multi-objective vehicle cooperative optimization controller and a safety controller.The multi-objective vehicle cooperative optimization controller is designed under the framework of distributed model predictive control to achieve vehicle safety and passenger comfort,formation control and fuel economy,while the safety controller is designed based on the safety invariant set.When the initial states of vehicle platoon are unreasonable or the large disturbances are harmful to vehicle safety,the safety controller will be used as an emergency brake to ensure vehicle safety.2)For the IVP driving on the road with constantly changing slopes,the vehicle cooperative optimization control strategy for maximizing fuel efficiency is proposed.In the vehicle cooperative optimization control strategy,the discrete gear ratio and the air resistance related to the vehicle spacing are considered,and an improved engine fuel consumption model that characterizes the engine driving,braking and idle modes is proposed;the 0-1 mixed integer linear programming algorithm is used to solve the constructed vehicle cooperative optimization problem for maximizing fuel efficiency.3)A robust vehicle cooperative optimization control strategy is proposed for IVP driving on a road with constantly changing slopes.In the vehicle cooperative optimization control strategy,the IVP is modeled as the high-order nonlinear dynamics model and the predessessor-following information topology is used;the concept of the band-stop function is first proposed and applied to the control strategy to enhance its robustness;to quickly solve the constructed robust vehicle cooperative optimization problem,after the minimum fuel consumption table and its corresponding optimal gear ratio table are obtained offline,the particle swarm optimization algorithm with multiple dynamic populations is given.4)A multi-objective high-speed vehicle cooperative optimization control strategy is proposed for IVP driving on a freeway with constantly changing slopes.In the high-speed vehicle cooperative optimization control strategy,the continuous gear ratio,the rotational inertia coefficient related to the gear ratio,the aerodynamic drag related to the vehicle spacing and IVP model constraints are considered;in order to quickly solve the constructed multi-objective high-speed vehicle cooperative optimization problem,an improved particle swarm optimization algorithm with multiple dynamic populations is proposed.5)For the intelligent electric vehicle platoon driving on a road with constantly changing slopes,a cooperative energy management strategy for multiple objectives is proposed.In the cooperative energy management strategy,the upper power demand prediction optimization problem for obtaining the optimal power demand prediction sequence and the lower HESS(Hybrid Energy Storage System)power split optimization problem for optimal power splits are constructed;to solve the constructed optimization problems,an improved particle swarm optimization algorithm with multiple dynamic populations,which can be used to solve the upper and lower optimization problems,is proposed.