Commuting-oriented Traffic Facility Configuration Methods For Urban Rail Transit Station Catchment Areas

With rapidly increasing urbanisation and motorization in China,large-scale cities have experienced population growth and the expansion of the urban spatial structure,workplaces and residences are becoming increasingly distant,and commuting times are increasing accordingly.Increased commute times not only increase costs for commuters but also affect their subjective well-Being(SWB).Meanwhile,the increase in household income has led to an increase in private car ownership,and residents are increasingly dependent on commuting by private car.Therefore,traffic congestion and air pollution caused by city expansion and motorisation have become urgent problems for the sustainable development of large cities in China.In this context,studying commuting-oriented traffic facilities configuration methods for urban rail transit station catchment areas can be used to provide the theoretical basis for improving different income groups’and different hukou groups’commuting.It is of great realistic significance and practical value to regulate car travel,guide public transport travel,improve the quality of public transport services and promote transit-oriented development(TOD).The data used for this paper were obtained from the 2014 China Labour-Force Dynamics Survey(CLDS 2014).Respondents were asked to rate their SWB on a five-point Likert-type scale,dependent variable,independent variables and controlled variables were determined.The prefecture-level cities in China were divided into three types:cities with urbanisation rate<50%,cities with 50%<urbanisation rate<70%,and cities with urbanisation rate>70%.Multilevel mixed-effects ordered probit regressions were applied to reveal commuting on resiednts’SWB based on urbanisation rate,hukou status(local residents with local hukou and migrants without local hukou).In accordance with China’s national statistical system,respondents’income were ranked from high to low,and divided into five equal parts using the equal division method,the top 20 percent and the bottom 20 per cent were respectively considered as the high-income group and the low-income group.Multi-level mixed-effects generalized linear model was used to reveal the relationship between the commuting time and urban characteristics/residents’income,and multi-level mixed-effects logistic regression was used to reveal the relationship between commuting modes and and urban characteristics/residents’income.Considering the close relationship between transportation and land use to promote TOD,a set of variables of traditional node-place model was adjusted and improved.Variables such as walkability and public transport accessibility level were introduced,and an imporved Node-Place model was proposed to classify urban rail transit station catchment areas.Characterized by the changes in the station choice behavior and the diversification of feeder modes under a mature state of the rail transit network,the traditional pedestrian-based TOD was improved.The enhanced TOD was adopted,that is,urban rail transit station catchment areas can be accessed by walking,cycling,and mini-bus service.Based on walkability,public transport accessibility level,service quality index,multi-criteria decision analysis was used to measure station attractiveness.An improved Huff model was established to determine the choice probability of each rail transit station,combined with the linear reference method to determine station catchment areas.Xi’an City was taken as an example to verify the proposed method,it was found that catchment areas of rail transit stations can be divided into six types to promote rail-based TODs,bicycle-and the mini-bus service-based spatial ranges of rail transit station catchment areas were obtained.In order to maximize the flexibility and convenience of mini-bus services,the potential demand index of urban road links was defined,and the potential demand reduction coefficient was introduced to reflect the competition and coopetition relationship between mini-buses and conventional buses in the same urban road link.Within the goal of maximizing potential commuting demand,a circular route model was developed to generate a mini-bus line connecting a rail transit station,and a genetic algorithm was employed to solve the model.The service area of mini-bus service was defined,and a mathematical model for mini-bus stop spacing based on Voronoi Diagrams was proposed to minimize commuters’total commuting time.An improved Wilson-Han-Powell sequence quadratic programming technique with global convergence and stability characteristics was applied,and the algorithm was programmed to solve the model using MATLAB software.Modification methods for mini-bus stop spacing that applicable to actual road traffic is proposed.Shanghai City was taken as an example to verify the proposed method,330m was the model results for stop spacing,along with modification methods,the optimal layout of mini-bus stop was obtained.Super high-rise buildings located in different rail transit station catchment areas were investigated,and internal and external environment of super high-rise buildings’parking demand were analysed.The main influencial factors,such as public transport accessibility level,floor area,and utility index of shared-parking were determined.The score range method was used to standardize these factors,and the corresponding reduction coefficient for parking demand was determined.A computational method was suggested to gradually reduce the parking requirements of ordinary buildings,with consideration of transit access,development intensity,and the overlap of activities.The reduction rationality of parking requirements for super high-rise buildings was verified under the constraints of public transport service capacity.Changqing tower of Xi’an City was selected as a case study,the results showed that parking requirements were 0.5 spaces/100m~2,which can effectively meet commuting demand of station catchment areas.Comparative analyses showed that parking requirements of existing super high-rise buildings generally does not exceed 0.5 spaces/100m~2,floats at around 0.3 spaces/100m~2 to 0.5 spaces/100m~2,which verified the rationality of the method.