Research On Design And Control Strategy Of Intelligent Driving Robot For Vehicle Road Test

In recent years,the demand for vehicle is increasing daily and millions of vehicles are manufacturing on yearly basis.The intelligent robotic driver is the best technology for new vehicles’ road-testing tasks.in this research,the focus will be on the development of robot-based driving technology and its implementation in the real world.This technology is a breakthrough innovation in driving automation and can help reduce the number of road accidents caused by human error during road testing.It can also reduce the amount of time needed for road trials and make it more efficient.The intelligent robotic driver will be able to sense the environment around it and take decisions based on the data collected.This will enable vehicles to drive in a more safe and more efficient manner.In addition,this technology will help reduce the cost of road testing,as it eliminates the need for human operators.the robot will imitate the human driving style and can be programmed to follow a set of predefined rules to avoid traffic violations and errors.The goal of this thesis is to design and develop an intelligent driving robot for an automatic transmission vehicle.The robot is designed using Solid Works,and different manipulators such as the steering manipulator,gear shift manipulator,and pedal manipulator are simulated using ADAMS software.The motion of each manipulator is controlled using a Simscape dynamic model with a PID controller and DC motor.The intelligent driving robot is designed to be used for road testing and is equipped with a camera sensor for object detection.The YOLO3 algorithm is used for object detection,including lane detection,road sign detection,and object detection.The first step in the design process was to create a 3D model of the driving robot using Solid Works.The model was designed to be compatible with an automatic transmission vehicle,and various manipulators were added,including a steering manipulator,gear shift manipulator,and pedal manipulator.Once the 3D model was complete,the next step was to simulate the motion of the manipulators using ADAMS software.Different steering manipulator,gear shift manipulator,and pedal manipulator motions were tested to determine the most efficient and effective movement patterns.To control the motion of each manipulator,a Simscape dynamic model with a PID controller and DC motor was used.The PID controller was used to ensure that the manipulators moved smoothly and accurately,and the DC motor provided the necessary power to move the manipulators.The Simscape dynamic model allowed for accurate simulation of the manipulator motion,which was essential for testing and refinement.The final step in the design process was to incorporate object detection capabilities into the driving robot.A camera sensor was added to the vehicle,and the YOLO3 algorithm was used for object detection.The algorithm was trained to detect lane markings,road signs,and other objects,allowing the driving robot to navigate the road safely and efficiently.There are 53 figures,8 tables and 69 references in this thesis.