This dissertation contends that the decision of the Municipality of Metropolitan Toronto and the Toronto Transit Commission to introduce a grid of frequent, all-day bus service on arterial roads in newly built, low-density suburban neighbourhoods is responsible for Toronto’s unique ability to attract suburbanites to transit. Toronto’s approach is in stark contrast with the that followed in most North American urban regions, where auto-oriented suburban built form is considered to make transit unviable, and therefore transit service outside the urban core is typically very limited. The Ontario government’s establishment of metropolitan government in the Toronto region in 1953, at a time when transit remained a popular mode of transportation, encouraged and empowered suburban politicians to pressure the TTC to expand service to their constituencies. In response, the TTC developed a plan for suburban bus service that succeeded, in terms of ridership and financial performance, far beyond its expectations. This success, in turn, encouraged further service improvements and government support for transit, producing a virtuous spiral of service increases, ridership gains, and government funding increases, which stood in sharp contrast with the vicious spiral of ridership declines, service cuts, and fare hikes that plagued transit systems in most North American cities. This dissertation is the product of archival research in Canada and the United States, as well as a series of interviews with policymakers, planners, and activists who were engaged during the period. The Toronto model offers valuable lessons for transportation planning across North America. It demonstrates that it is possible to achieve high transit mode share, even in areas that are not designed as explicitly transit-oriented communities. This means that it is possible to shift trips away from the automobile without needing to entirely rebuild the suburban neighbourhoods where most North Americans reside, an unachievable goal on the timeline required to avert catastrophic climate change. It also demonstrates that the benefits of large capital investments in rapid transit and rail projects will only be maximized when paired with operating funding to ensure that the new infrastructure is embedded in a broader network of frequent local transit service.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts

The Metropolitan Atlanta Rapid Transit Authority (MARTA) Transit Oriented Development (TOD) program has been expanding the number of stations being considered for development of surface parking lots and into the air rights over certain rail stations. As of 2015, MARTA has six rail stations in various stages of TOD development, which will increase multi-modal options for metro Atlanta residents. The overarching goal of TOD development is to increase transit ridership and reduce auto-dependency; hence quantifying the potential benefits of TOD development in terms of ridership is paramount. Despite several drawbacks, travel demand models have historically been utilized to forecast ridership for land use changes and transit improvements. Direct ridership models (DRMs) are transit demand forecasting methods that can be applied to land development in cases where traditional travel demand models (TDMs) are not well suited. DRMs leverage geographic tools commonly used by planners to take advantage of small scale pedestrian environment factors immediately surrounding transit stations. Although DRM data and methods can achieve greater precision in predicting local walk-access transit trips, the lack of regional and large-scale datasets reduces the ability to model ridership generated from riders outside the immediate vicinity of the rail stations. Stations that have high multi-modal access trips, particularly via personal vehicle and connecting buses, are not typically accounted for by DRMs. Hence, this study focuses on pedestrian-based rail boardings only, a metric that also allows the use of a large scale onboard survey distributed by the Atlanta Regional Commission (ARC) in late 2009 and early 2010 in Atlanta, Georgia. Analysis of the large scale on-board ridership survey also reveals variables that may be useful in forecasting ridership at the station level when coupled with available census data. Comparison of variables such as income, age, gender, ethnicity, and race from census data with the large scale survey guided the selection of candidate variables to be included in a DRM for MARTA rail stations. Results from the comparison showed that using census data in DRMs does not always accurately reflect the ridership demographics. Notable differences in pedestrian-based ridership and transit catchments appear to occur in populations making less than $40,000, African American populations, and the young and elderly populations. Large differences in the survey and census data reported around the stations raise questions about the usability of census data in predicting ridership at rail stations. Despite the shortcomings of using census data to directly predict walk access transit ridership, an ordinary least squared (OLS) regression model predicts a high proportion of variance of pedestrian-based ridership in Atlanta, Georgia. A small number of variables were incorporated into a DRM to show the strong relationship of employment density with pedestrian based ridership. The number of low income residents was also influential in increasing ridership via walk access.

Community and Regional Planning / In the past two decades, Austin has tremendous population growth, job opportunity in the downtown core and transportation challenges associated with that. Public transit, and particularly rail, often is regarded as a strategy to help reduce urban traffic congestion. The Urban Rail, which combines features of streetcars and light rail, is introduced into Austin as a new transit rail. The City of Austin, Capital Metro and Lone Star Rail are actively studying routing, financial, environmental and community elements associated with a first phase of Urban Rail. This thesis collected 2010 Origin and Destination Rail Transit Survey data from Capital Metropolitan Transportation Authority. The research focuses on the rail transit ridership. Two regression models are applied to analyze the factors influencing Austin rail transit ridership. One model is focusing on the socioeconomic characteristics. One model is focusing on the spatial factors. Our model shows that demographic factors have more significant effect than spatial factors. In addition, this work also tries to analyze the correlations between those factors and make recommendations based on the analysis result. / text

Master of Landscape Architecture / Department of Landscape Architecture/Regional & Community Planning / Blake Belanger / Investigating historical trends of public transportation, two distinct groups of riders are targeted. First, individuals living and working in large metropolitan centers, and second, people who are dependent upon public transit; referring to people who cannot afford personal automobile transportation, possess no driver’s license, or are physically unable to drive (Garrett and Taylor, 1999). Analyzing the national demographics related to age and poverty levels, transit dependents make up only approximately 25% of the United States population. Expanding transit ridership will make our nation’s transportation sector more sustainable. Public transportation systems yield exceptional benefits including economic and community vitality, gasoline consumption reduction, air quality improvement and diverse cultural interactions promoting social cohesion (Metro Transit- St. Louis, 2010). This report focuses on ridership potential in the Rock Island Corridor, an unused rail thoroughfare in Kansas City. Local governing organizations are analyzing the corridor for future commuter rail implementation. In order to attain higher ridership and ensure long-term viability, the commuter rail must attract residents that are not dependent upon public transportation. This project maps transit dependencies along the Rock Island Corridor looking at income levels, home values, and commuting distance. The findings illustrate that Lee’s Summit is not dependent upon public transit and has tremendous potential to impact the ridership and development direction along the corridor. Looking into the future of the corridor the time to plan is now. Lee’s Summit is expected to see a population increase of 40,636 people (a 50% increase) by the year 2040 (Mid-America Regional Council, 2010). The strategies applied to Lee’s Summit are applicable to other similar suburbs of Kansas City, ultimately making Lee’s Summit a catalyst for the region. The organization of the project is focused around three major sections. The first section explores and analyzes current public transit practice in terms of ridership and aesthetics. The second section explains a three-part strategy focused around a park-n-ride and a transit-oriented development, both supported by a municipal feeder bus system. The third section demonstrates design and program ideas for the park-n-ride station that provide the community with visions to promote smart growth and a sustainable future.

Cities like New York and Chicago have comprehensive heavy rail networks that provide not only high frequency service, but also reach popular destinations and employment centers. Although many other cities strive for similar transit infrastructure, acquiring the financial backing and/or right-of-way to develop these transit systems can take years. To develop transit systems in a more timely and cost-effective manner, cities are using alternative transportation modes such as light rail, streetcars, bus rapid transit (BRT), and frequent local buses. As cities become more multi-modal, their system maps become more confusing. Historically, systems have provided separate transit maps for each transit mode they provide. However, integration of these new modes requires integration of system maps. Experts in the field of transit mapping have been calling for frequent transit maps, which highlight routes that provide frequent service or reach important destinations, regardless of mode. Some cities have implemented these multi-modal maps successfully, but to date, there is no documented guidance to assist agencies in creating these maps. Using Metropolitan Atlanta Regional Transit Authority (MARTA) in Atlanta as a case study, the research team created multiple maps that include three transit modes throughout the city and tested them through surveys on transit riders and non-riders. Each map adds BRT and local bus routes that meet specific frequency and/or location criteria to the existing rail map. This project examines reactions of transit riders and non-riders to these new multi-modal, schematic maps. Through surveys targeting individuals with different transit ridership habits, this project explores the potential to affect ridership on these alternative modes and enhance system understanding beyond the rail map. The results of these surveys demonstrate the need to simplify system maps, the public desire for frequency mapping, and the potential to increase ridership on alternative modes. These results build on previous work that schematic maps affect rider spatial understanding of the system and route or mode decisions. Including more modes on the map in an efficient and visually pleasing way, results of this project found that both riders and non-riders would take transit more and better understand how all of the modes interact together to form a comprehensive transit network.

This thesis evaluates how municipal transit ridership in mid-sized cities is influenced by external factors. External factors are forces outside a municipality’s direct control but potentially affect the municipality in some way, in particular its transit ridership. The thesis also determines the appropriateness of municipal levels of response to each factor. Two mid-sized municipalities in Ontario, Canada – the City of Kingston and Region of Waterloo – were studied. The evaluation, first, identifies the trends or “current conditions” between the municipalities and five sets of external factors to determine influence on ridership. The factors are 1. Population Growth and Density; 2. Demographics (Seniors, Students and Immigrants); 3. Regional Location; 4. Federal/Provincial Impacts; and 5. Fuel Prices. Second, the municipality’s level of response was measured in three ways. Staff awareness of the factor and its influence was gauged using key informant interviews and municipal councillor surveys conducted by the researcher. Internal policy and guidance documents measured whether policies relating to each factor are appropriate. Finally, observations of implemented initiatives determined whether they appropriately deal with each factor. The study finds that more external factors act on Waterloo than Kingston. Therefore, Waterloo has strong incentives to prioritize – among many municipal responsibilities – its transit system and to focus on increasing ridership. The strongest incentives for Waterloo are population growth, the student demographic and federal/provincial impacts. Kingston has only one strong incentive: the senior demographic. The study also finds that Waterloo has appropriate levels of response to more of the external factors than does Kingston. Recommendations for Kingston and Waterloo are provided for improving their levels of response to each set of factors. The paper concludes that municipal size is an important driver, but internal levels of response are critical success factors. The data analysis matrix developed for this study can be used by other municipalities to help identify appropriateness of internal responses as they relate to the influence of external factors within their municipality.

Public transit is a key method for increasing sustainability in the transportation sector; transit can decrease emissions harmful to the environment and increase social equity by providing improved mobility. Given the limited resources available to build and operate public transit, it makes sense to meet multiple sustainability goals simultaneously. Transit that is accessible by non-motorized means and serves multiple trip types can potentially reduce vehicle usage and increase mobility for everyone. This research assesses whether transit systems with high non-motorized access rates and non-work trip usage are meeting social and environmental goals and what factors impact non-work and non-motorized access rates. Eight criteria were used to choose 17 metropolitan regions that represent a range of transit conditions in the US. Non-parametric correlations were calculated between non-work usage and non-motorized access and a dataset of 30 continuous and 11 categorical variables that measure regional characteristics, transit efficiency, land use, rider demographics, and transit operations and design. In-depth case studies, including site visits and interviews, were done for Denver, Colorado; Minneapolis/St. Paul, Minnesota; and Sacramento, California. The correlations and case studies both confirm that transit system with high non-work usage and non-motorized access are not meeting social or environmental sustainability goals. These systems primarily serve low-income riders, are less well funded, and provide limited service. Only systems with higher per capita funding levels meet social goals and higher funding is correlated to higher income riders. However, having higher income riders does not imply that social goals are met. Regional policies regarding operations and design of transit can increase usage for non-work trips and non-motorized access and are necessary to ensure both social and environmental goals are met.

Transit ridership analysis has been advancing towards the use of disaggregate spatial and boarding data. This study attempts to improve the understanding of factors influencing transit ridership by estimating/comparing ridership models at the route, the segmented route, and the stop level in the Austin area. Spatial and statistic analysis methods are used in this study. The dependent variable is ridership at the transit route, the segmented route, and the stop level, whereas independent variables consist of traveler characteristics, land use, transit service characteristics, and other contextual factors. Spatial analysis is conducted using Geographic Information System (GIS) to compile data within a quarter-mile buffer from each transit stop, each segregated route, and each route. Linear and semi-log models of ridership are estimated using Statistical Analysis System (SAS). Initial analysis confirms the qualitative understanding that traveler demographics such as population and employment densities, ethnic background, and income significantly affect transit ridership. Land use composition, measured by the shares of single-family homes, multi-family homes, commercial, civic uses, as well as the total area of paved parking, all influence transit use. Service qualities such as headway and transfer opportunities also matter. Sensitivity tests of these factors affecting ridership are carried out to compare model performance among the route, segmented route, and the stop level analyses. It is expected that the study findings will help to better inform transit agencies and local communities in optimizing existing transit operations, planning for new services, and developing transit-friendly environments. Primary data were obtained from the Capital Metropolitan Transit Authority and the Census Bureau, and secondary data was processed by GIS analysis. / text

Understanding transit usage has become a critical transportation research interest and policy goal. This thesis presents results of an analysis of the 2001 NHTS data specifically focusing on the newly released appended variables that measure access or distance to public transportation. Statistically significant public transportation distance intervals from households and individuals were chosen for analysis in relation to other key variables in the original dataset. Actual relationships between public transportation and traditional household and person characteristics nationwide are explored, specifically focusing on both rail and bus transit modes for the work commute trip. Geographically, both inclusions and exclusions in analysis are conducted due to the widely accepted ubiquitous transit network present in the NY region. The analysis reveals strong differences in household and workplace access to transit as a function of race, income, auto ownership, and urban area size. Additionally, a very high sensitivity to access exists suggesting that the share of transit accessible trips is smaller than previously acknowledged. Approximately 53 percent of households are within aviimile of bus service and 40 percent within a quarter-mile. Approximately 10 percent of the population lives within one mile of rail. Over 50 percent of workplaces are within a quarter mile walk radius of a bus line. Not surprisingly, work is more closely concentrated near transit than are residences. Furthermore, mode share for transit declines approximately two thirds beyond the first interval beyond 0.15 miles from a bus route. These observations imply a high value to services in close proximity to residential areas.Historical work in this topic area include geographically specific data analysis obtained from surveys which potentially allow a degree of subjectivity in perceived responses whereas accessibility and distance data analyzed in this thesis are actual and spatially measured. Additionally, a regression model exploring the significance of actual access to transit upon mode choice is performed to explore the significance of influence by measured access variables. The analysis suggests that access is even more critical than might have previously been acknowledged by the transit planning profession.