Research On Analysis And Optimization Of Older Drivers’ Behavior Characteristics

With the acceleration of aging population and the improvement of social development in China,the number of elderly drivers and their driving demand are rising.Because of the aging,elderly drivers’ physiological enervation resulted in the high probability of traffic accidents.To solve this problem,this paper uses the KMRTDS driving simulator,Ergo LAB physiopsychological instrument and I-view HED4 eye tracker to collect the data of the driving behavior.Based on the analysis of the difference in driving behavior characteristics between elderly and young drivers,this paper established a training model using a driving simulator to provide relevant theoretical support for elderly drivers’ safety education and optimize their driving behaviors.First,VS-Design software is used to set up two sets of road traffic virtual experiment scenarios for driving behavior analysis and training respectively.Forty healthy participants were recruited to complete the experiment.The data of eye movement,psychophysiology,driving behavior,vehicle operation and the driving attitude scale were collected in the experiment.Secondly,the difference between elderly and young drivers are analyzed after determining the statistics of driving behavior indicators.The results show that there are differences in driving behavior between elderly and young drivers.The main performance is that the ability and speed of elderly drivers to obtain traffic information are less than those of young drivers.In addition,the abilities of elderly driver to control the vehicle shows greater volatility than those of young driver.Thirdly,the moment and degree of driving behavior occurrence are used as coding element to construct the driving behavior characteristic map in different situations.The map can intuitively express driving behavior and qualitatively analyze difference between elderly and young drivers in time dimension.Then,the longest common sub-sequence(LCSS),difference discrimination indicator of maps,is employed to quantitatively measure the difference between elderly and young drivers in time dimension.The results show that due to the increase of age and the decline of physical functions,the driving behavior nodes of elderly drivers are later than those of young drivers,and elderly drivers need more time to obtain traffic information.Therefore,elderly drivers show less alertness of danger,higher load of traffic information and more nervousness,which makes them have higher driving fluctuation and dangerous driving tendency when driving vehicles.Finally,based on the results of comparative analysis and spatiotemporal analysis,and using the theory of planned behavior(TRB)as a framework,a driving simulator-based training mode is proposed from three levels of “perception,norm,execution” to optimize driving behaviors of elderly drivers.And the validity of the training model is proved by comparative analysis.At the same time,the structural equation model(SEM)was used to capture the complex relationship between training level,driver characteristics and traffic safety.The results show that the positive effect of training level on driving behavior characteristics is higher than the negative effect of age on driving behavior characteristics,indicating that participating in training can improve the driving behavior characteristics of eldly drivers to a certain extent.The negative effect of training level on dangerous driving tendency is higher than the positive effect of age on dangerous driving tendency,indicating that participating in training can reduce the dangerous driving tendency of eldly drivers to a certain extent.