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Research On Lateral Tracking Control Strategy Of Unmanned Vehicle Considering High-low Speed And Road Curvature

Posted on:2023-03-06Degree:MasterType:Thesis
Country:ChinaCandidate:Z B LiuFull Text:PDF
GTID:2542307073489784Subject:Vehicle Engineering
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As one of the important links of Intelligent Traffic System(ITS),unmanned vehicle can fundamentally solve the problems of safety,environmental protection and convenience when people use cars,and improve transportation efficiency and traffic conditions,so it has been widely concerned and studied by people.At the same time,the lateral tracking control is one of the key technologies of unmanned vehicle.In the complex road environment,it is very important to propose a reasonable lateral tracking control method for different vehicle speeds and varying road curvature,so considering the road curvature,this thesis studies low-speed lateral tracking control strategy,high-speed lateral tracking control strategy,and high-low speed switching stability control strategy.The main contents of this thesis are as follows:First,a co-simulation platform is established by Pre Scan,Carsim and Simulink,including the vehicle dynamics model and the road scene model.In order to improve the accuracy of lateral tracking control,a continuous adaptive segmental fitting method for reference paths based on cubic Bezier curves is proposed.At the same time,the model predictive control algorithm is designed to provide stable longitudinal speed control.The above establishes the foundation for the later study of the lateral tracking control algorithm.A low speed unmanned vehicle lateral tracking control strategy is proposed and verified by simulation.When the traditional pure pursuit algorithm(Pure Pursuit,PP)is used for lateral tracking in narrow and complex scenes(such as parking lots and alleys)at low speed,the inappropriate selection of the look-ahead distance will affect the stability and accuracy of lateral tracking.In addition,the "cutting-corner" problem occurs when the vehicle goes from a small curvature to a large curvature.In response to these problems,an improved pure pursuit algorithm(Improve Pure Pursuit,IPP)is proposed: search for a look-ahead point based on the relative position of the vehicle to the reference path,vehicle speed and road curvature.In view of the phenomenon of " cutting-corner " when the vehicle enters a corner with a large curvature from a small curvature,select the look-ahead point outside the reference path,and the final look-ahead point is used to calculate the steering wheel angle and apply it to the vehicle,thereby improving the tracking accuracy of the low-speed lateral tracking algorithm.A high speed unmanned vehicle lateral tracking control strategy is proposed and verified by simulation.Considering yaw,side slip and curvature,the vehicle dynamics model was established,and the MPC controller was designed to improve the stability and accuracy of high-speed lateral tracking by taking into account the constraints of vehicle slip stability,road environment and tire longitudinal and horizontal coupling force,aiming at the quadratic optimization of heading deviation and lateral deviation in the process of high-speed tracking.In order to improve the accuracy and stability of the lateral tracking of unmanned vehicles at full speed,a control strategy include low speed,high speed and a switching stability control strategy was proposed.,reference paths containing different road characteristics were built in Pre Scan for simulation verification.Finally,an intelligent driving vehicle platform was established to verify the effectiveness of part of the lateral tracking control strategy,and campus roads were selected to verify the IPP control algorithm.The results are compared with reference of Fuzzy Logic control Pure Pursuit(FPP)and Vehicle control Pure Pursuit(VPP).
Keywords/Search Tags:Unmanned vehicle, Continuous adaptive curve fitting method, Full speed unmanned lateral tracking control strategy, Pure pursuit control, Model predictive control
PDF Full Text Request
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