Research On Lateral And Longitudinal Cooperative Control Of Intelligent Vehicle Platoon Based On Vehicle Networking

While bringing us convenience,automobiles also bring a number of problems,such as significant traffic congestion and the problem of energy exhaustion.Intelligent transportation system research can effectively solve these problems.As a major participant in intelligent transportation systems,vehicles traveling in formation can not only reduce wind resistance,but also interact with other vehicles in the platoon and road terminals at the same time through advanced vehicle networking technology and fusion sensing technology to make more accurate control based on this information and improve the safety and comfort stability of the vehicles of the members of the platoon on the road.Therefore,it has a very broad development and practical prospects.The current research on vehicle platooning mainly focuses on longitudinal control and is dominated by kinematic and inertial delay models.However,because the vehicle itself is a complex strongly coupled system,the lateral forces and longitudinal forces during the vehicle motion are coupled with each other and affect each other.Therefore,in this paper,after introducing the key technologies for the study of intelligent vehicle platoons,the three-degree-of-freedom monorail vehicle model is developed according to the dynamics of the vehicle.And the nonlinear term of the magic tire formulation is reasonably simplified based on the small angle assumption.The final vehicle dynamics model based on linear tires is obtained.In view of the complexity of vehicle driving conditions and the problem that the control accuracy and algorithm robustness are degraded by external disturbances and modeling parameter uptake,this paper designs a control strategy combining neural network algorithm and sliding mode control method.The network weights are replaced by the estimated values of the minimum parameter learning method,and the RBF neural network is used for adaptive compensation of external disturbances and modeling parameter uptake to improve the robustness of the algorithm,and the internal stability and system stability of the control algorithm are proved based on Lyapunov’s stability theorem.In order to solve the problem that the ant colony algorithm is easy to find the local optimal path,this paper uses genetic algorithm to optimize it,and uses the crossover and variation function of genetic algorithm to generate better path solutions and finally obtain the shortest path.The trajectory is smoothed using the cubic spline curve,and the smoothed path is tracked at different driving speeds using the cooperative control algorithm proposed in this paper.The robustness of the control algorithm is investigated based on Matlab/Simulink for the modeling uncertainty and external disturbances of the vehicle.The robustness of the control algorithm is demonstrated under the influence of time-varying travel speeds of vehicles,heterogeneous vehicle platoons,homogeneous and heterogeneous parameter uptake,and external noise disturbances.Mathematical simulation records show that the transverse-longitudinal cooperative control strategy designed in this paper can ensure the safety and comfort stability of the vehicle platoon trajectory driving,and has favorable robustness under the influence of multiple uncertainty disturbances.