Research On Control Algorithm Of Driver Robot For Vehicle Trial

Vehicle durability test is an indispensable part of vehicle development.However,the traditional vehicle durability test requires a lot of human resources,It is difficult to carry out durability test under harsh and dangerous scenes,and the consistency of every operation can not be guaranteed,which reduces the reliability of test data.Driving robot just makes up these defects.With the maturity of driverless and other related technologies,driving robot has gradually become irreplaceable in the vehicle durability experiment,and it has been able to complete most of the tests independently.The control process of driving robot can be divided into three steps.Firstly,the surrounding environment and its own positioning are sensed by sensors,and the information is transmitted to the central controller,then generating the optimal control command to maintain the desired trajectory through control strategy,Finally,the controller sends the control command to the actuator,which controls the steering wheel,accelerator and brake pedal of the vehicle to complete the autonomous test task.the second step is the main research of this paper,that is,designing the control strategy to generate the control command.The main work of this paper is summarized as follows:1.Establishing the driving robot experimental platform.The driving robot can be divided hardware and software parts According to different function,For the hardware part,this paper briefly introduces the hardware composition of the driving robot,including on-board sensor and actuator,but this paper focuses on the working principle,installation,calibration and navigation data acquisition of the integrated navigation system.For the software part,this paper introduces the ROS development platform,which is favored by developers because of its powerful function integration and easy to operate.2.Design the control strategy of driving robot.This paper designed the lateral control strategy and longitudinal control strategy respectively.The lateral control strategy is to make the vehicle close to the desired trajectory under various scenarios and conditions,in addition,maintain the body stability and human comfort during driving.The longitudinal control strategy is to make the vehicle driving with the desired speed.As to the specific of realizing lateral control,in this paper,the current mainstream control methods are compared and analyzed from the mathematical principle,simulation results and various factors.Finally,LQR is selected as the lateral controller.In the vertical control.As to longitudinal control,considering the good performance of PID and the small occupation of computing resources,therefore,PID is regarded as the core of the longitudinal control.3.Verifying the performance of algorithm on the simulation platform and vehicle platform.For lateral control simulation test,three groups of tests are conducted,Firstly,this paper analysis the control accuracy on different roads,then make vehicle accelerate on circular loop and curved roads at constant speed.Whether the performance is good or bad is evaluated from the following two aspects: the deviation of vehicle with the desired trajectory and driving smoothness.For the longitudinal control simulation test,making the vehicle to approach the target speed at different initial speeds on the straight road section,uphill road and downhill road,and the control performance was evaluated from the speed maintenance accuracy after vehicle was stable and control smoothness during shifting.Then jointing the lateral and longitudinal control and making vehicle across a complex road with speed limit,After simulation analysis,the effectiveness of the control algorithm is verified by using the driverless vehicle developed in our laboratory.