Research On The Strategy Of Smart Car Control System Considering Surrounding Vehicles

In recent years,frequent traffic accidents caused by heavy traffic and man-made traffic have become a major obstacle to the normal operation of the road traffic system.Intelligent vehicles have received more and more attention and have become a research hotspot in this field due to its advantages of improving traffic efficiency and reducing driving errors.As a single agent driving on the road,intelligent vehicles are an indispensable research topic for intelligent vehicles.The research on decision-making control considering the status of surrounding vehicles includes considering the front and rear vehicles and considering the left and right vehicles.In this paper,the following researches is conducted for the current situation that the control system rarely considered the surrounding vehicles.First of all,in order to facilitate the unilateral control method research and simulation analysis of the vehicle,the vehicle motion is analyzed according to the research content of the subject,and a kinematic model based on the geometric characteristics of the vehicle's lane change trajectory and vehicle speed is established according to Newton's law of dynamics and a three-degree-of-freedom dynamic model of the entire vehicle based on dynamic characteristics such as longitudinal control and lateral control of the vehicle.Secondly,based on the model,a longitudinal control method is proposed that takes into account the state of the front and rear vehicles to adjust its own driving state.Using the new artificial potential field theory,taking the front and rear target vehicles as the center of the two potential fields,a mixed force function in the full situation force field is constructed,and the parameters are set according to the speed and distance information to make the vehicle in the front and rear target vehicles in the middle Driving in a safe area with zero field force not only avoids rear-end collisions,but also increases road utilization and reduces congestion in crowded conditions.Experiments have confirmed the ideas,which made up for the disadvantages of the existing adaptive cruise system that only considered the vehicle in front,and also filled the gap of applying the new artificial potential field to the longitudinal control of the intelligent vehicle.Then,in view of the defects of the control system that only considers the state of the front vehicle or the state of the rear vehicle,when the rear vehicle approaches continuously or the front vehicle brakes suddenly,it still lead to a rear-end accident,we proposed a set of lane change systems that included determining lane changing hazard,predicting lane changing hazard,planning lane changing trajectory,etc.Besides,we also designed an increased acceleration time-to-collision(TTC),when encountering a dangerous situation,if it is impossible to avoid rear-end collision by adjusting the distance to the front and rear vehicles,choose to change lanes under safe conditions.The state of the pre-lane vehicle should be taken in consideration when changing lanes.If the lane change is allowed,re-enter the adjustment environment of the front and rear vehicles after the lane change is completed.Finally,the feasibility of the system control method considering the driving status of surrounding vehicles was verified by MATLAB / Simulink software simulation analysis and the joint simulation analysis of PreScan and MATLAB / Simulink software.Using the " Chery Erez 5e" Intelligent automobile as a test platform,through setting the typical working conditions,we also verified the feasibility and reliability of the longitudinal decision control method proposed in this thesis that considers the state of the front and rear vehicles to adjust its own driving state.