Modeling And Evaluating The Influence Of Approaching Vehicles On Pedestrian’s Crossing Characteristics At Unsignalized Crosswalks

Reducing interference between different traffic participants at uncontrolled pedestrian crossings and guiding pedestrians to cross the street safely and efficiently while reducing the risk of pedestrian crossing is an urgent issue to be addressed.This study,supported by the National Natural Science Foundation of China(No.52172338)and the National Natural Science Foundation of China Youth Science Foundation Project(No.51908060),focuses on the behavior and eye movement characteristics of pedestrians crossing the street at the large number of unsignalized crosswalks in cities under the influence of approaching vehicles as well as micro pedestrian flow simulation models under.The main structure of the paper consists of four parts: pedestrian crossing experiment design,pedestrian crossing behavior characteristics and group differences analysis,pedestrian crossing eye movement characteristics and leaderfollower fixation transfer characteristics research,and pedestrian crossing traffic flow simulation model construction considering surrounding traffic participants.The main research content includes:(1)Analyzing the impact of approaching vehicles on pedestrian behavior characteristics.Based on the pedestrian crossing traffic data collected by drone aerial video at unsignalized crosswalks and analyzing the traffic flow conditions at the experimental site,the driving characteristics of vehicles were obtained.The differences in pedestrian crossing speed and acceleration with and without approaching vehicles were studied,and the effects of the speed of approaching vehicles and the relative distance between pedestrians and approaching vehicles on pedestrian speed and acceleration were further explored using mathematical statistics methods.Finally,starting from the pedestrian group crossing,the self-organizing phenomenon was analyzed,and the influence of approaching vehicles on the movement behavior of different groups crossing the street was discussed through statistical analysis of the movement characteristics of leaders and followers in the pedestrian group.(2)Analyzing the changes in pedestrian crossing eye movement characteristics.By collected eye movement data of experimenters during pedestrian crossing experiments using an eye tracker,the characteristics of eye movement behavior during crossing were analyzed.The areas of interest were divided based on the main objects of interest that pedestrians may pay attention to when crossing the street,and the projection points of pedestrians in each area of interest and the duration of each fixation point were counted.What’s more,the paper studied whether the presence of approaching vehicles would affect the areas of interest of pedestrians and what influence the speed of approaching vehicles and the relative distance between pedestrians and vehicles would have on their eye movement behavior.Considering the different roles in the pedestrian following phenomenon,the differences in visual perception characteristics between leaders and followers were studied,and the changes in scanpaths during the crossing process of different roles were analyzed.(3)Proposing a cellular automata model based on dynamic field of view range,effects of pedestrian group internal and pedestrian-vehicle interaction.Based on the analysis results of pedestrian crossing eye movement characteristics,the concept of pedestrian dynamic field of view range was established and introduced into the social force model,considering the social force generated by other traffic participants within the pedestrian dynamic field of view range.The parameters in the social force model were calibrated based on pedestrian motion and gaze behavior survey data,and a cellular automata model that can describe the movement of pedestrians and vehicles under the interaction of pedestrians,vehicles and surrounding traffic participants was established.