Study Of The Basic Theory And Application Of Catchment Area Of Urban Rail Transit Stations

Along with the ongoing urbanization and motorization in China, traffic congestion, accidents and air pollution have become more and more seriously, which severely restrict the social and economic development of Chinese cities. Facing with these challenges, "Transit Priority" has been proposed as a national strategic in China. At the same time, the concentration effect of population in urban area, the increase in residential trips, as well as the prolonging of travel distance require urban public transportation systems to provide urban residents with safe, reliable, fast and comfortable services. Therefore, increasing transport capacity, improving the level of service, and enhancing the competitiveness and attractiveness of urban transit by, for example, developing low-carbon, efficient, and high-capacity transit systems, have become a necessary component for urban sustainable development. Under these backgrounds, developing urban rail transit has become an inevitable choice for super and big cities in forming an efficient urban public transportation system with clear mandate division and mutual cooperation. Facing with the rapid development of urban rail systems in China, the present paper treats the basic theory and application of catchment area of rail transit stations as the research focuses, founded by The National High Technology Research and Development Program of China (2007AA11Z202), The Graduate Research and Innovation Project of Jiangsu Province (CXZZ110165), The Excellent PhD Student Award of Ministry of Education, The Scientific Research Foundation of Graduate School of Southeast University (YBPY1405) and The Chinese Government Graduate Student Overseas Study Program (201306090063), by adopting classic and mature models and approaches, the present research does studies mainly as follows:First, this paper analyzes the development and ridership of rail transit systems in China at the national level, as well as analyzes the mode share of rail transit ridership in overall transit ridership at the urban level. Considering independent variables measuring urban and systematic attributes, this paper establishes models for forecasting rail transit lines’ capital cost, ridership and cost-effectiveness. In addition, this paper compares ridership and cost-effectiveness between modes of urban rail transit (heavy rail, light rail, and Maglev) in China and between countries of China, United States, and Turkey. Study results from this chapter provide urban planners and policy makers with basic data support to understand the capital cost, ridership and cost-effectiveness performance of rail transit systems in China, as well as provide basic background for the following chapters of the present paper.Second, by considering traveler characteristics (gender, age, household income, occupation, etc.), trip characteristics (travel time, trip purpose, etc.), especially rail station properties (station forms (ground station, underground station), station functions (ordinary, transfer, or terminal), the number of feeder buses, the distance of station to the city center, the road length within station-area, etc., this paper establishes models to determine the catchment area of rail transit station based on pedestrian walking distance. The established model provides urban planners and managers with references to improve the travel environment within certain station-area, as well as to improve the attraction and the level of service of urban rail systems.Third, taking rail transit station ridership and station to station ridership as research objectives, based on the brief review of existing studies on rail transit ridership, this paper establishes direct demand forecasting models for analyzing rail transit ridership at station level and station-to-station level. The established models reflect the practices of rail transit systems in China and emphatically consider the potential factors that might affect rail transit ridership within the catchment area of rail transit stations, which provide rail transit planners and mangers with key technical supports for ridership prediction and analysis.Fourth, combined with the multi-objective of developing rail transit systems (passenger attraction, environment protection, engineering feasibility and operational efficiency), this paper establishes fuzzy multi-objective decision support model for elevating and selecting urban rail transit planning alternatives, which comprehensively reflects the factors measuring the catchment area of rail transit stations. The model provides rail transit planners and decision-makers with basic method for elevating and selecting the best rail transit planning alternatives.Fifth, by comprehensively considering household characteristics, personal characteristics and travel features that might affect residents’ trip mode choice (walk, bike, bus, rail transit, and car), this paper examines the impacts of household and travel OD location (particularly the proximity effects of near the catchment area of rail transit station) on residential trip mode choice, and establishes a multinomial logit (MNL) model and a nested logit (NL) model to analyze residential trip mode choice. The established models can be used to quantitatively analyze the impacts of the introduction of rail transit on residents’(in particular, the residents within/near the catchment area of rail transit stations) trip mode choice. Moreover, the paper establishes a MNL model to examine the relationship between household stated preference for vehicle purchase and proximity to the catchment area of rail transit stations.Sixth, this paper analyzes the role of rail and bikesharing integration (R+B) in expanding the traditional catchment area of rail transit stations that based on walking distance and in resolving the last-mile problem of rail transit systems, explores the differences in bikesharing travel time and trip chain by gender and by day of the week, as well as realizes the visual analytics of bikesharing trip chain by gender and by day of the week. In addition, this paper recommends measures for improving the level of service and the integration efficiency of R+B.Overall, reflecting the fact of the rapid development of rail transit in China and considering the characteristics of Chinese rail transit systems, this paper establishes:1) predicting model for analyzing rail transit capital cost, ridership and cost-effectiveness, by considering factors measuring urban and systematic attributes; 1) OLS model for framing the catchment area of rail transit stations, particularly reflecting the characteristics of travelers, travel and stations; 3) direct demand forecasting models for analyzing rail transit station and station-to-station ridership based on the consideration of rail transit’ catchment area; 4) fuzzy multi-objective decision support model for elevating and selecting urban rail transit planning alternatives; 5) MNL and NL models for analyzing residential trip mode choice, as well as MNL model for analyzing residential vehicle purchase; and 6) method for realizing the visual analytics of R+B integration trip chain. The models developed in this paper can be used by urban planners and managers as references for understanding the catchment area of rail transit station in China, as well as for analyzing and forecasting rail transit ridership, elevating and selecting rail transit planning alternatives, analyzing residential trip mode choice, and promoting the integration between rail transit and bikesharing.