Research On Unsafe Riding Behavior Of Urban Cyclists

With the advent of the era of sharing economy in China and the improvement of people’s awareness of environmental protection,bicycles have returned to the public’s vision for their flexibility,convenience,non-pollution,high accessibility,and the ability to effectively solve the “last mile” problem,becoming an important part of the urban transportation system.However,due to the high population density,complex road environment and large loopholes in the management of non-motor vehicles in China,the number of bicycle traffic accidents is increasing year by year,turning into a major hidden danger threatening the safety of the transportation system.As the direct operator of the bicycle,cyclist’s specific behavior has a direct impact on driving safety.In the process of behavioral decision-making,the cyclist obtains information from the outside world through the sensory system,processed by the brain to form a decision,which is also a process of mental activity.Therefore,in order to discover the mechanism of unsafe cycling behavior from the root cause,it is necessary to study the influencing factors of unsafe cycling behavior from the psychological level,and propose targeted strategies to provide theoretical support for improving the driving safety of self-propelled vehicles.Firstly in the paper,cyclists were taken as the research object to analyze the generation process,psychological factors as well as classification of unsafe cycling behaviors,and behavior theory;secondly,revealed preference survey and state preference survey were used to conduct data investigation on the basic personal information,unsafe cycling behaviors and unsafe cycling behavior intentions of cyclists.SPSS23.0 was adopted to conduct reliability analysis,validity analysis,descriptive statistical analysis,and group difference analysis of the questionnaire data;then,a theoretical model of unsafe cycling behavior based on the theory of planned behavior and the theory of protective motivation was put forward,and the corresponding assumptions were made.The GLS method in the structural equation model was used to estimate the parameters of the model,and at the same time the goodness of fit of the model and the rationality of the hypothesis were verified;finally,the data were classified based on gender,and they were respectively substituted into the behavioral theory model for comparison and analysis according to the path coefficient differences,so as to formulate corresponding behavior management policies.Through a comprehensive analysis of the paper,it is found that unsafe cycling behaviors can be divided into two categories: bad habits and violations.Moreover,because of the conceptual overlap between the “perceived behavioral control” factor in the theory of planned behavior and the “self-efficacy” factor in the theory of protective motivation,it can be used as a prerequisite for the combination of theories.Through data analysis,the paper found that among the five attributes of cyclists,there is the largest behavioral difference on the gender level,and there are significant differences between the two types of people in the behaviors of checking mobile phones,using the same vehicle for two people,and drunken cycling.Through model verification,the paper found that behavioral intentions are greatly influenced by behavioral attitudes,subjective norms,risks,and perceived behavioral control.Bad habits are more likely to be affected by behavioral intentions,and violations tend to be affected by perceived behavioral control.Furthermore,the model verification and result analysis were carried out for the gender layer with the largest behavioral difference.It was found that the behavioral intentions of male cyclists are mainly affected by behavioral attitudes,subjective norms,and response efficiency,while those of female cyclists are basically influenced by threat risks and perceived behavioral control.Therefore,we can develop strategies to improve unsafe cycling behaviors for groups of different genders.Among them,three measures of building a closed-loop cycling education,establishing an unsafe cycling behavior display platform,and increasing punishment intensity are more obvious in reducing unsafe cycling behaviors of male cyclists.Improving the allocation of transportation resources and holding cycling accident simulation activities are more obvious in reducing unsafe cycling behaviors of female cyclists.Constructing a “human-machine integration” supervision system and increasing rewards for safe cycling have an equal impact on male and female cyclists.