Research On Intelligent Vehicle Change Method Based On Vehicle Networking Information

In recent years,cars have gradually become the most frequently used means of transportation in people's daily life.The growth rate of possession is persistently high.Although the country continues to invest heavily in building roads,it still cannot improve the complicated traffic conditions.Traffic jams and traffic accidents are coming.It becomes a major concern for people to travel.With the development of technology,autonomous driving technology has gradually become the direction of future car development.Among them,automatic lane changing technology is one of the most critical and challenging issues for automatic driving.However,the current research on the automatic lane changing method is based on the self-sensor to obtain the external information,and can not get the surrounding vehicle motion information and is limited to the static path planning.The assumed state of the lane-changing vehicle is still not in the whole lane-changing process.The actual road conditions are mostly complex and variable road conditions.The lane change vehicles need to adjust their speed and position to ensure safety in time.Therefore,this paper proposes an automatic lane change method based on vehicle networking information.Smart cars use the Internet of Vehicles and sensors to sense the driving environment.The sensors include millimeter-wave radar,GPS,camera and laser radar to obtain information about the surrounding environment of the vehicle.These raw data are integrated in the“sensor data fusion module”,and the car network transceiver unit Receive real-time information on the vehicle network to obtain dynamic and static obstacle information.The real-time data of the vehicle network is used to re-plan the path according to the environmental change information around the vehicle.The system plans a dynamic driving track with high safety,comfort and high efficiency according to the real-time information of the obstacle.This paper first analyzes and summarizes the research on path planning and lane changing methods at domestic and foreign,and selects the characteristic parameters of lane changing time and acceleration to represent the efficiency and comfort of lane change respectively to establish the objective function.Then,based on the completion of the cubic polynomial preliminary planning path,the road boundary conditions and the surrounding vehicle motion state are analyzed,and the minimum safety distance method is used to ensure safety.Finally,the optimal lane change trajectory is solved according to the boundary conditions,the objective function,the starting and ending conditions,and the model kinematics and dynamics are controlled by the model predictive control and the adaptive fuzzy controller layer,so that the tracking control is realized to realize the automatic lane change.The main research contents of this paper are as follows:(1)Build the objective function model.Acceleration is the main reason for affecting comfort.Therefore,acceleration must be considered in consideration of comfort.In addition,the lane change time not only affects the traffic efficiency of the vehicle but also affects the entire traffic operation.The lane change time is shorter,the the traffic efficiency is higher.The impact of traffic operations is smaller.(2)The establishment of the optimal dynamic lane change trajectory model.Using the cubic polynomial,constraints and objective function to solve the optimal lane change trajectory,and can refer to the lane change trajectory according to the real-time information provided by the Internet of Vehicles,the real-time data update can be timely fed back to the decision-making unit to re-route when the sudden situation is about to occur in front.The lane change vehicle adapts to changes in the surrounding vehicle motion state.(3)Design of model predictive control and adaptive fuzzy controller.Firstly,the vehicle two-degree-of-freedom model is built,and the model predictive control is introduced to control the vehicle tracking and planed path.At the same time,it can meet various constraints and real-time problems.At the dynamic level,the direct adaptive confusing controller is used to control the driving torque,and the double is adopted.Closed loop structure which enables simultaneous trajectory tracking and control of drive torque.(4)Automatic lane change simulation and real vehicle verification in multi-vehicle dynamic environment.Firstly,the multi-vehicle lane change scenario is designed,and then the simulation is carried out by using Carsim and simulink to verify the feasibility and rationality of the method.The results show that the method is feasible.Then the real vehicle verification is carried out.By analyzing the experimental data and comparing with the simulation results.It is found that the tracking error is always within the range of 0.15m,and the parameters such as speed and yaw rate are within the constraint range.The maximum acceleration value during the lane change is not greater than2m/s~2.It can ensure the comfort during the process of changing lanes.The model established in the paper is more reasonable.