Research On The Visual Behavior Of Cyclists In Urban Flat Intersection

In recent years,with the increasingly prominent problems of the urban environment,traffic jams,energy,and security,the promotion of bicycle traffic has gradually become a development trend of urban transportation.The development of bicycle transportation makes the bicycle traffic safety problem particularly important.Most of the cyclists' perceptions of the road traffic environment originate from vision.In urban roads,there are a lot of interference and conflicts at level crossings.The road traffic environment is relatively complicated and it easily leads to traffic accidents.Therefore,it is necessary to study the visual behavior of bicycle cyclists in urban level intersections.Based on the summary of the domestic and foreign related research results,the cyclists visual behavior and the basic form of the parameters are described and analyzed in the system,to determine the number of fixation,the average fixation duration and the number of saccade,the average saccade duration,and saccade angle,horizontal viewing angle distribution,and vertical viewing angle distribution as the perspective the basic parameters of rider visual search mode.Select typical urban roads,including T-shaped intersections and cross intersections as experimental roads,select 20 bicycle cyclists as test subjects,and use the Dikablis eye movement meter to develop a “bike” experiment to collect various eye-movement data.Based on the statistics of experimental data of different characterization parameters,the following three aspects were analyzed on the eye movement characteristics and regularity of cyclists at urban level intersections.(1)Through the estimation of bicycle cycling speed and field tests,it is determined that the speed range of the cyclists studied in this paper is defined at 5-15km/h,and the average speed of cyclists passing through the intersection is divided into two categories: 5-10km/h and 10-15km/h,and compared the fixation behavior and saccade behavior of cyclists through different intersections under two types of riding speeds.(2)Divide the horizon of the bicycle cyclist and separately count the attention ratios from the horizontal and vertical angles when passing through different intersections under two types of riding speeds.(3)One-way analysis of variance(ANOVA)was applied to each eye movement index data using Spss,and the eye movement index selected in this paper was significantly different at two different riding speeds.The use of fuzzy theory to classify bicycle cyclists' visual search patterns.By standardizing the average eye movement parameters of different cyclists,a fuzzy similarity matrix and a fuzzy equivalent matrix are established.With reference to the riding speed,driving age,and gender of each cyclist,the best classification threshold is determined and the cyclist's visual search pattern is determined.It is divided into four categories: Excellent,Good,Medium,and Poor.Using Spss statistical analysis software to perform single-factor analysis of variance on the visual data of the four types of riders,the significant level of eye movement index is less than 0.05,so the result is reliable and the established model is feasible.