Modeling On Driver Group's Steering Manipulation Laws

With the popularization and development of vehicle techniques,the total number of the drivers has been gradually increasing,and the driver's driving skills are becoming more and more diversified.Considering the same driving task,drivers with the different driving skills usually present different vehicle manipulation performance.In this way,how to consider the wide driving crowd's driving behaviours within the initial vehicle design process,providing an good vehicle ease-of-control performance is a hot research topic for researchers in recent years.Moreover,an accurate grasping of the wide driving crowd's driving behaviours is also important for the intelligent and personalized development of the vehicle.The paper aims at establishing an mathematical model being capable of characterizing the wide driving crowd's steering behaviour laws,i.e.,the steering control driver model with the driver group's steering maneuvers,studying the steering control laws of the wide driving crowd as well as its influences on the closed-loop path-following performances,to provide a simulation method using for the adaptability analysis of vehicles to drivers.In particular,the "driver group manipulation laws" can be explained as the discreteness as well as randomness of the wide driving crowd's vehicle maneuvers: the discreteness characterizes the differences of maneuver behaviours due to drivers' various driving experiences or skills;the randomness characterizes the uncertainty of behaviors owning to the external environmental interferences,drivers' physiological and psychological factors,and so on.The main contents and conclusions are as follows:1.Modeling on typical driver steering control behaviors.Based on the Model Predictive Control(MPC)theory,three typical steering control maneuvers of the drivers,including the road preview,steering wheel angle decision and steering wheel manipulation are modeled.In the road preview modeling process,a multi-point previewing strategy is used to characterize the driver's behavior of obtaining the desired path information from road ahead.Within the steering angle decision modeling process,the linear two DOF vehicle model groups with the equivalent cornering stiffness as variables are proposed to characterize the drivers' cognition behavior to the different vehicle dynamic characteristic,which are used as predictive models,and then MPC steering control rules are derived.Within the modeling process of the steering wheel manipulation,the hysteresis effect of the driver's neuromuscular system is modeled by a time delay element.Through modeling on typical driver steering manipulation,the typical driving behaviors,including the preview,decision and the execution of a driver are revealed,which lays foundations for study on the steering control driver model with the driver group's steering maneuvers.2.Solution to the typical driver steering control model.In accordance to the state space method,two solving strategies,including the analytical and numerical ones are used to solve the typical driver steering control models.During the analytical solving process,the optimal steering wheel angle is obtained via derivation.As for the numerical solution,the constraints featuring the real drivers' physiological restrictions are established,and a primal-dual active set quadratic programming method is utilized to obtain the optimal steering wheel angle.The proposed model is validated via simulation and the comparison results with the two methods under different driving conditions indicate the superior precision and speed of the numerical solution.3.Modeling on driver group steering control behaviors.Based on the previously derived typical driver steering control model,the steering maneuver considering the discreteness and randomness of the wide driving crowd is modeled.Wherein,the driver's cognition behaviors to the vehicle states are investigated and a tire side slip angle perception model is proposed.For this model,driver's cognition to vehicle lateral dynamics are described as the perception to the tire side slip angle,whose perceived side slip angle is a random variable subject to the Gaussian distribution,the mean of which is corresponding to the real side slip angle and the variance characterizes the driver's steering skills and the nonlinear vehicle lateral dynamics.Eventually,the parameters of the tire side-roll angle model are identified via the real driver's double-lane change vehicle trajectory data.4.Validation and discussion on the group steering control model.To verify the proposed group driver model,a Car Sim-MATLAB/Simulink co-simulation platform is built.Through the comparisons of the simulated and the real vehicle trajectory database envelope regions,the statistics of the vehicle trajectory errors,the results show that the proposed group driver steering control model is accurate.Based on this model,the steering manipulation laws of the skilled and novice driving crowds are discussed.The results manifest that faced with the same path tracking tasks,the skilled driver is more accurate and stable than the novice driver,and the tracking performances will decrease with the increase of the vehicle lateral dynamics nonlinearity.5.Vehicle ease-of-control evaluations.With the group driver steering control model,the simulation method for vehicle ease-of-control evaluation is studied.Wherein,a performance evaluation criterion with considerations of driving safety and vehicle closed-loop response is established.Through the simulation tests,a database of the performance evaluation criterion is built.Based on the statistics of the criterion data,more excellent ease-of-control evaluation results for vehicles with understeering characteristic are determined,and the rear wheelbase is optimized to realize the best performance of vehicle with the understeering characteristic.In this paper,the behavioral characteristics of the typical drivers',including the preview,decision making and the execution in the steering task is accurately modeled,furthermore,a mathematical model is derived to characterize the discreteness and randomness of the wide driving crowd,which lays a theoretical foundation for the digital,intelligent and personalized development of the vehicle.