This qualitative comparative case study examined factors related to politics that might explain the notably different active transportation (AT - walking, cycling, and public transit use) rates achieved in Helsinki, Finland (a leading European city in AT, where 77 per cent of people use primarily AT for daily transportation) and Ottawa, Canada (a leading North American city in AT, but where the AT rate is 28.5 per cent). Applying the Advocacy Coalition Framework (ACF) - a policy process theory - individual focused interviews were conducted with 47 active transportation experts from the two cities. Document review was employed as a secondary method. The results are discussed in three articles written for peer reviewed journals – the first two concentrating on the findings from Helsinki and Ottawa respectively, and the third article comparing the findings from both cities. Overall, differences stemming from the ACF category of relatively stable parameters (i.e., stable background-level factors) including land use, transportation planning traditions, and political systems were identified as likely important in explaining the discrepancy in AT rates.

The transportation sector is considered one of the major contributors to greenhouse gas (GHG) emissions in metropolitan areas, and any efforts to reduce these emissions requires strategic management of multiple transportation modes. This paper presents a method to identify opportunities to reduce GHG emissions by expanding commuter bus services and incentives to shift commuters from private cars to transit. The approach uses a nested multinomial logit model for mode choice in a region that includes driving alone, carpooling, walking, cycling, and using four possible transit modes (ferry, commuter rail, rapid transit and bus) by walk access or driving access. A model of existing conditions was calibrated with data from the Boston metropolitan area. Using an emission factor model based on average speeds from the California Air Resources Board (CARB), the net effect of new commuter bus service on GHG emissions from transportation was estimated. Potential GHG reductions are weighed against the capital and operating costs of new transit services to quantify the cost-effectiveness of a new commuter bus service for isolated origin-destination pairs. This modeling framework is used to optimize fares and bus frequency in order to identify the corridors with the most cost-effective potential for GHG reduction. Results are presented for the Boston region, demonstrating the feasibility of implementation and the potential magnitude of benefits for cost-effectively reducing GHG emissions associated with transportation. The method is general and can be applied in other cities around the world.

While there are many proposals for fixing congestion between San Francisco and Oakland in California by adding a new bridge or tube, these solutions will take decades to implement even though a solution is needed now. This thesis assesses sixteen different strategies for reducing congestion in the short-term in the four categories of improving transit, promoting carpooling, implementing intelligent transportation systems practices, and incentivizing alternatives to using the Bay Bridge. Top priorities include HOV improvements on the West Grand Avenue and Powell Street onramps, altering WestCAT Lynx and BART transit services, partnering with rideshare apps to increase transit station accessibility (last mile problem), partnering with vanpool/minibus apps, promoting carpooling and implementing a citizen report system for carpool violators, shifting corporate cultures away from requiring employees to drive and drive alone, and lastly, altering land-use planning practices. To reach this conclusion, an inventory of current proposals and relevant research was compiled. Ridership and capacity data for the various modes of transportation across the bay were assessed for shortfalls and opportunities. Through this research and its resultant conclusions, focus can be placed on the best strategies to pursue in the near-term, while the Bay Area waits on a second bridge or tube in the long-term.

abstract: Moderate physical activity, such as walking and biking, positively affects physical and mental health. Outdoor thermal comfort is an important prerequisite for incentivizing an active lifestyle. Thus, extreme heat poses significant challenges for people who are outdoors by choice or necessity. The type and qualities of built infrastructure determine the intensity and duration of individual exposure to heat. As cities globally are shifting priorities towards non-motorized and public transit travel, more residents are expected to experience the city on their feet. Thus, physical conditions as well as psychological perception of the environment that affect thermal comfort will become paramount. Phoenix, Arizona, is used as a case study to examine the effectiveness of current public transit and street infrastructure to reduce heat exposure and affect the thermal comfort of walkers and public transit users. The City of Phoenix has committed to public transit improvements in the Transportation 2050 plan and has recently adopted a Complete Streets Policy. Proposed changes include mobility improvements and creating a safe and comfortable environment for non-motorized road participants. To understand what kind of improvements would benefit thermal comfort the most, it is necessary to understand heat exposure at finer spatial scales, explore whether current bus shelter designs are adequate in mitigating heat-health effects, and comprehensively assess the impact of design on physical, psychological and behavioral aspects of thermal comfort. A study conducted at bus stops in one Phoenix neighborhood examined grey and green infrastructure types preferred for cooling and found relationships between perception of pleasantness and thermal sensation votes. Walking interviews conducted in another neighborhood event examined the applicability of a framework for walking behavior under the stress of heat, and how differences between the streets affected perceptions of the walkers. The interviews revealed that many of the structural themes from the framework of walking behavior were applicable, however, participants assessed the majority of the elements in their walk from a heat mitigation perspective. Finally, guiding questions for walkability in hot and arid climates were developed based on the literature review and results from the empirical studies. This dissertation contributes to filling the gap between walkability and outdoor thermal comfort, and presents methodology and findings that can be useful to address walkability and outdoor thermal comfort in the world’s hot cities as well as those in temperate climates that may face similar climate challenges in the future as the planet warms. / Dissertation/Thesis / Doctoral Dissertation Sustainability 2019

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A thorough understanding of transit customers’ preferences and travel behaviour is fundamental to offering a high-quality urban transportation system. The dominant approach in transit quality literature is rooted in understanding current transit users’ preferences. However, disregarding the heterogeneity in transit customers’ desired quality yields suboptimal conclusions regarding their preferences. Therefore, an effective transit system should strive to understand the broad spectrum of transit and non-transit users’ preferences to increase transit ridership. Towards that end, this research aims at deciphering the heterogeneity associated with transit customers’ service desired quality. The research utilized a primary dataset elicited from an online survey that was part of Hamilton Street Railway (HSR) Public Engagement efforts in Hamilton, Ontario, Canada. The research employed state-of-the-art discrete choice models (e.g., error components logit models, latent class choice models, nested logit models) along with multivariate statistical and spatial analysis. In this respect, this dissertation quantified and unveiled latent heterogeneity in transit customers’ preferences and its implications on their willingness to pay for service improvements through various techniques and specifications. Unlike the conventional classifications for transit customers, our research classifies transit customers into three latent segments: Direct Trip Enthusiastic (DTE), Cost-Sensitive (CS), and Real-time Information Supporter (RIS). The dissertation also investigated and further quantified the influence of subjective psychological factors in shaping transit customers’ preferences towards service attributes. For instance, environmental consciousness is found to be associated with less sensitivity to walking time while higher appreciation to at-stop real-time information provision. Furthermore, the research highlighted how the built environment and its contextual effects influence customers’ travel behaviour while accounting for variations in socioeconomic characteristics. The spatial analysis concluded that the built environment's influence is not equally efficacious over geography. Overall, this research presents a unique contribution to the knowledge of public transit research for practitioners, policymakers, and academia. / Dissertation / Doctor of Philosophy (PhD)

This study investigates the effect of rainfall on transit performance measures at the route level in the Puget Sound region of Washington State. Transit agencies are required to report certain performance metrics to the Federal Transit Administration (FTA), but performance measures can also be used to evaluate service and provide customers with information regarding the transit system. Using a three-year sample of archived automatic vehicle location (AVL) and hydrologic data the relationships between ridership, travel time, delay, and rainfall were investigated. The analysis of daily ridership and rainfall resulted in no statistically significant results, however, the results are supported by the existing research in this field. There was a generally negative trend in ridership with respect to rainfall. The analysis of travel time and rainfall did not result in the expected outcome. It was hypothesized that travel time would vary with rainfall, but that was not always the case. During many rainfall events the travel time remained average. The analysis of delay and rainfall shows that the impact of rainfall on delay is more complex than assumed. The delay during dry trips was different than the delay during light and moderate rain, but during heavy rain the statistical different disappeared. These results, implications for transit operators, and future research opportunities are discussed.

Natural or man-made disasters result in unfortunate events around the nation every year. Such extreme events necessitate the short-notice or no-notice evacuation of a large population from the stricken area. This research presents an optimization modeling technique to develop an evacuation plan for transit-dependent residents during no-notice disaster situation. The proposed plan relies on the application of existing public transit system of an urban area. The public transit routing plan (PTRP) problem is formulated as a mixed integer linear program. The PTRP identifies the optimal routes for transit vehicles to move evacuees from the danger zone to designated safe destinations. A heuristic TABU search algorithm is used to find high-quality solution in a reasonable amount of time. Finally, DYNASMART-P is used to evaluate the effectiveness of the developed PTRP. Numerical experiments are conducted using the traffic network of the city of Fort Worth, TX, to illustrate the proposed modeling technique.

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