Sustainable public transit investments: increasing non-motorized access and multiple trip type usage

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.Ph.D.Committee Chair: Dr. Michael Meyer; Committee Member: Dr. Adjo Amekudzi; Committee Member: Dr. Beverly Scott; Committee Member: Dr. Catherine Ross; Committee Member: Dr. Laurie Garro

Bus rapid transit as a neoliberal contradiction

Bus Rapid Transit (BRT) is being implemented as a neoliberal project, but it creates contradictions that challenge the premise of neoliberalism. BRT projects are affordable rapid transit infrastructure, but they are also an impetus to restructure the urban bus sector in developing cities with informal mass transport. The dominant model of BRT implementation creates a market for bus service from large private companies where the government takes on the risk and brands the service as part of the city\u27s attempt to be a ‘world class’ city that can attract mobile capital. However, BRT and the formalization of the bus sector can increase the power of urban residents by firmly putting transport in the public sphere; workers by increasing the incentives for collective action; and bus riders by prioritizing space for buses over cars. But these are only openings that require action to take advantage of the contradictions

Meeting Multiple Sustainability Goals: Non-Motorized Access and Non-Work Trip Usage on Public Transit

Transit designed to serve multiple trip types accessed without vehicles can meet social and environmental sustainability goals simultaneously. Seventeen representative U.S. cities are used to examine transit systems with high non-motorized access and use for non-work trips. Non-parametric tests are used to determine correlations with indicators of social and environmental sustainability. The median income of riders is significant and negative for both variables. Higher non-work usage and non-motorized access does not imply that social and environmental goals are met. Higher-income riders are needed to meet both goals, but having high-income riders does not ensure social goals are met

The publicness of public transport: The changing nature of public transport in Latin American cities

Public transport can be ‘public’ in multiple ways and without specificity when one public aspect changes there is no way to consider the impacts of that change. Currently there is a process of transit formalization taking place in Latin American cities that is changing the publicness of their systems. This paper identifies four publicness types- public space, public goods, public ownership, and public concern- and discusses the implications of transit projects in Santiago, Bogotá, Quito, and Mexico City on all four. While the impacts are not heterogeneous, governments are recognizing transit as a public good and introducing public funding and public ownership of Bus Rapid Transit and other infrastructure. These changes have the potential to strengthen public transit\u27s role as public space and are increasing transit as an issue of public concern, but there has been little formalization of public participation in the process. Public transit is now a three way relationship between private operators, government agencies, and the community, but most of the focus in this new arrangement has been on the contracts between the operators and government and less attention has been paid to the relationship with the public

Estimation of Short-Term Bus Travel Time by Using Low-Resolution Automated Vehicle Location Data

Estimation of short-term bus travel time is an essential component of effective intelligent transportation systems (ITS), including traveler information systems and transit signal priority (TSP) strategies. Several technologies, such as automated vehicle location (AVL) systems, can provide real-time information for estimation of bus travel time. However, low resolution of data from such technologies presents a challenge to accurate estimation of travel time. Several models for estimation of bus travel time at signalized urban arterials were developed and tested. These models used low-frequency AVL data and required only knowledge of network specifications such as locations of bus stops and intersections. First, a linear regression model was developed; it decomposed total travel time into its components, including running travel time, dwell time at bus stops, and delay at signalized intersections. Second, various machine learning models, including support vector regression (SVR) with nonlinear kernel, ridge, Lasso, decision tree, and Bayesian ridge were trained by using Python libraries such as scikit-learn and evaluated. A segment of Washington Street in Boston, Massachusetts, was selected as the study site. The results indicate that the SVR model outperformed other regression models in generalized error measures, in particular those of mean absolute error and root mean square error. The findings of this study can lead to improved traveler information systems and more-efficient TSP strategies and, overall, can contribute to better transit quality of service

What is behind fare evasion in urban bus systems? An econometric approach

Fare evasion is a problem in many public transport systems around the world and policies to reduce it are generally aimed at improving control and increasing fines. We use an econometric approach to attempt explaining the high levels of evasion in Santiago, Chile, and guide public policy formulation to reduce this problem. In particular, a negative binomial count regression model allowed us to find that fare evasion rates on buses increase as: (i) more people board (or alight) at a given bus door, (ii) more passengers board by a rear door, (iii) buses have higher occupancy levels (and more doors) and (iv) passengers experience longer headways. By controlling these variables (ceteris paribus), results indicate that evasion is greater during the afternoon and evening, but it is not clear that it is higher during peak hours. Regarding socioeconomic variables, we found that fare evasion at bus stops located in higher income areas (municipalities) is significantly lower than in more deprived areas. Finally, based on our results we identified five main methods to address evasion as alternatives to more dedicated fine enforcement or increased inspection; (i) increasing the bus fleet, (ii) improving the bus headway regularity, (iii) implementing off-board payment stations, (iv) changing the payment system on board and (v) changing the bus design (number of doors or capacity). Our model provides a powerful tool to predict the reduction of fare evasion due to the implementation of some of these five operational strategies, and can be applied to other bus public transport systems