Intelligent Vehicle Tracking Control Based On DGNSS/INS Integrated Navigation System

Along with the rapid development of the contemporary and improvement of the people's living standards,the vehicle population continues to increase,the problem of energy crisis and environmental pollution stands out.New technology of automobile intelligence such as energy-saving and emission-reduction technology,self-driving technology,artificial intelligence technology have become an strong voice and desire of the people with a series of stringent environmental policies and vehicle safety regulations introduced.Automotive intellectualization has become a global hot spot,and the driverless car is undoubtedly the peak of the high point.A driverless car is a complex system incorporating automatic control,architecture,artificial intelligence,visual calculation and so on.This paper is to research on vehicle tracking navigation control.Firstly,it is necessary to locate the position of the vehicle accurately and quickly for a driverless car.At present,there are many positioning products,most of them are serve for drivers,and drivers themselves have multiple cognitive abilities,they can correct the error of a few meters or even more than ten meters which accuracy is far from enough for a driverless car by their own vision.So,we use DGNSS/INS integrated navigation for the location of the driverless car.It not only overcomes the problem of single satellite navigation is easy to be obscured and the location drift problem existing in single inertial navigation,but also improves the accuracy and stability with RTK difference position technology.Secondly,the EV with 4 Independently-driving Wheels model that contains the vehicle kinematics model,the 3-DOF vehicle body dynamics model,the GIM tire model,and the drive system model is established.Then,the comparison testing with CarSim vehicle model have been completed,and the test results prove the rationality and validity of the model.The model lays a foundation for later studies.Force on the design of two tracking controllers using Model Predictive Control(MPC)algorithm,which are respectively apply to low speed condition and high speed condition.The accuracy of controller trajectory tracking is mainly considered in low speed.So simulation experiments on straight line and circular trajectory respectively were carried out.It is proved that the controller can maintain good tracking accuracy under different speed conditions.It is necessary to consider the vehicle stability besides the accuracy of track tracking in high speed.So,we carry out simulation experiments on straight line and double line trajectory respectively.In linear trajectory tracking simulation experiment,we find that the controller can maintain high tracking accuracy at different speeds.In double lane track,we proved that the controller can keep good stability in different adhesion coefficient,controller parameter,vehicle speed.Finally,a vehicle test to verify the portability of the MPC controller was carried out according to the existing experimental platform.