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Study On The Overflow Behavior Of Non-Motorized Traffic Participants Waiting To Cross The Street And The Influence Mechanism

Posted on:2024-01-11Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhangFull Text:PDF
GTID:2542307157469874Subject:Transportation
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Pedestrians and cyclists,as vulnerable groups in traffic,are susceptible to injury in traffic conflicts.It has been observed that pedestrians and cyclists commonly congregate near the greenbelt waiting to cross the street.The safety island effect formed by the greenbelt induces pedestrians and cyclists to spill out of the delineated waiting area and exit to wait near the greenbelt to cross the street,and this behavior increases the probability of conflict risk between pedestrians,cyclists and motor vehicles.In order to further clarify the influence of factors such as the greenbelt on the crossing overflow behavior of pedestrians and cyclists and its influence mechanism,this paper selects six intersections in Xi’an,Shaanxi Province,to obtain research data by means of video filming and questionnaire surveys,and uses quantitative analysis methods to explore the internal and external influences on the crossing overflow behavior of non-motorized traffic participants,as well as to evaluate the negative external effects generated by the crossing overflow behavior of non-motorized traffic participants and propose management strategies.The paper uses YOLOv5+Deep Sort to extract the trajectory data of pedestrians,cyclists and motor vehicles,and selects Passing Distance(SP)as a negative externality measure to evaluate the negative externalities of pedestrian and cyclist spillover behaviors;establishes a binary logistic regression model to explore the external influence mechanism of non-motorized traffic participants’ waiting spillover behaviors;uses a structural equation modeling analysis questionnaire to explore the human influence mechanism of nonmotorized traffic participants’ waiting spillover behaviors.The study shows that:(1)At intersections with greenbelts,the proportion of potential hazardous conflicts arising from the interaction between non-motorized traffic participants and motor vehicles in the overflow area is greater,and the proportion of potential hazardous conflicts arising from the interaction decreases as the location of the completed greenbelt is further from the crosswalk,with a strong negative correlation between the two.(2)Six external influences significantly affected the spillover behavior of non-motorized traffic participants waiting to cross the street: the distance between the greenbelt and the pedestrian crosswalk and curb,age,the type of non-motorized traffic participants,whether they carry heavy objects and whether they observe the traffic flow while waiting,among which non-motorized traffic participants are prone to spillover behavior when the distance between the greenbelt and the pedestrian crosswalk and curb is close;cyclists and slightly older non-motorized traffic participants are prone to spillover behavior;non-motorized traffic participants who carry heavy objects and do not check the traffic flow are prone to spillover behavior.(3)Non-motorized traffic participants who are pressed for time and do not know the compliance waiting area are more likely to engage in spillover behavior;non-motorized traffic participants are more likely to engage in spillover behavior when they believe that the greenbelt is protective,or when they feel less pressure from public opinion,or when their families and friends have positive attitudes toward standing in the non-safety area and waiting to cross the street.The research results of this paper help traffic managers understand the internal and external causes of pedestrians’ and cyclists’ crossing waiting spillover behaviors and propose targeted solutions to reduce the probability of potential hazards for non-motorized traffic participants waiting to cross the street and improve road safety.
Keywords/Search Tags:Greenbelts, Non-motorized traffic participants, Spillover behavior, Binary logistic model, Theory of planned behavior, Structural equation modeling
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