| The safety of automated vehicle is directly correlated with how skid-resistant the road surface is.It is required to examine both the adhesion properties of the tires and the road surface’s skid resistance in order to evaluate the friction characteristics between the two surfaces.This paper begins the research from several angles,including the analysis of pavement skid resistance influence factors,tire model establishment,adhesion coefficient estimation,and simulation application,in order to address the issue of characterizing the microscopic skid resistance of pavement in decision planning of automated vehicles and its application to pavement conditions with variable friction characteristics.First,different skid resistance evaluation indices from macroscopic and microscopic perspectives—construction depth and friction coefficient—are proposed in order to examine the impact of pavement skid resistance features on the safety of automated vehicles.The structure depth model is created,and the structure depth is chosen as the base parameter of the pavement friction characteristics model.Dry,wet,and water pavement friction characteristics models are created,respectively,by combining the water film thickness and other pavement skid resistance related parameters,and the obtained friction characteristics parameters are applied to the motion control of the automated vehicle.To investigate how pavement anti-skid qualities affect vehicle braking stability,researchers employ the Carsim vehicle braking test.Second,using the tire test data from FSAE TTC,the two-level parameters of the PAC2002 tire model are determined in order to create a tire model that takes the friction characteristics of the road surface into account.By suggesting a method to characterize the tire-road surface friction characteristics in the PAC2002 tire model based on the peak friction coefficient scaling factor,an improved tire model(ASMF Tire)based on vehicle speed,slip rate,and road surface condition is established that can characterize the comprehensive skid resistance of the road.Tire dynamics simulation identifies the curve of the tire-road adhesion properties.Again,for all-weather automated vehicle decision control,reliable estimate of tire-road adhesion coefficients is necessary.In order to obtain the vehicle dynamics response data,a seven-degree-of-freedom vehicle dynamics model is built using the ASMF Tire model.From this model combined with the μ-S curve principle combined,a trace-free Kalman filter algorithm is used to build a filter estimator that estimates the peak adhesion coefficient of the road surface.For the estimate algorithm’s validity and accuracy,four simulated pavements—high adhesion,low adhesion,docked pavement,and docked pavement—are built up.Finally,the application method of pavement microscopic skid resistance parameters in self-driving vehicles is proposed.An adhesion coefficient judgment module is developed to combine the adhesion coefficient estimated in real time with the skid resistance information of the road ahead obtained from vehicle-road interaction,and actively select a reasonable adhesion coefficient value as the input condition for future decision control.Taking a typical automated driving scenario-automatic emergency braking system as an example,a test scenario under a variable adhesion coefficient road surface is set up,and the effectiveness and accuracy of decision control for automated vehicles using tire-road inter-adhesion characteristics is verified through joint simulation of Matlab/Simulink and Carsim.The simulation results show that the proposed improved AEB control strategy based on the coefficient of adhesion prediction and judgment method can ensure the safety of the vehicle under different test scenarios and road conditions. |
