| Commuting is an important component of urban transportation.The traffic demand of commuting and the private vehicle ownership keep increasing as the economic growth and urban expansion.However,the new construction of transportation infrastructure and the improvement of transportation services have been unable to keep up with the growing demand for commuting traffic,which lead to a series of problems,such as traffic congestion,traffic accidents and energy waste.In order to solve these problems,it is an effective way to advocate the use of the public transportation with low energy consumption and less land occupation from traditional high-energy-consumption and high-pollution private vehicles through transportation demand management.As the rail transit is an essential component of public transportation,this thesis takes the rail transit as a typical representation of public transportation to analyze its influence on the mode choice of commuting.Considering the impact of private vehicles,the service levels of rail transit and the built environment on the mode choice of commuting,this thesis investigates the influencing factors that promote the transfer of commuting mode from private vehicles to rail transit from three aspects: private vehicles,rail transit and the built environment.Firstly,the basic commuting trip data for the residents in Nanjing City are obtained through questionnaire surveys,and the obtained data are analyzed with SPSS software to preliminarily investigate the commuting characteristics of the commuters with private vehicles and rail transit.In addition,the built environment data obtained from the authorities are analyzed with Arc GIS software to obtain the built environment index data.Secondly,considering the influence of psychological factors on the transfer of commuting mode,a Rasch model is established to analyze the satisfaction of rail transit passengers on the access facilities and the intention of private vehicle users transferring to rail transit.The influencing factors of the transfer from private vehicles to rail transit and the impact of personal attributes on the mode choice are analyzed from two different aspects,i.e.,the private vehicles and the rail transit.On this basis,the percentile method is used to extract the thresholds for the key influencing factors.Next,due to that commuters usually have a low perception on the built environment at both of the residences and workplaces in the process of commuting,this thesis analyzes the factors on the built environment with a mode choice model and obtains key elements on the transfer of commuting mode.A threshold surface method is used to extract the thresholds of these elements.Finally,combined with the aforementioned studies,the impact factors affecting the transfer of private vehicles to rail transit are summarized,and the “push policy”,the “pull policy” and the “power policy” to promote the transfer from private vehicles to rail transit are proposed from the perspective of private vehicles,rail transit and built environment,respectively.Compared with existing studies in the literature,this paper combines the Rasch model and the mode choice model to analyze the key factors that affect the transfer from private vehicles to rail transit from multiple aspects,including the private vehicles,the rail transit,and the built environment.At the same time,the percentile method and the optimized threshold surface method are used to quantitatively analyze the key factors and extract the threshold values.Besides,this paper also starts with the personal ability obtained from the Rasch model to analyze the difference on the commuters,and proposes personalized policy recommendations for different commuters.Through this research,this paper obtains the key factors that affect the transfer from private vehicles to rail transit,and extracts thresholds for these key factors.On this basis,policy suggestions to promote the transfer from private vehicles to rail transit are proposed from three aspects,i.e.,the private vehicles,the rail transit and the built environment. |
