Fostering environmentally friendly transport solutions for tourists lies at the core of the strategiesaimed at implementing sustainable tourism transportation. In this sense, this study aims toidentify the determinants of green mobility choices taken by young adults and adults to travel toand from their holiday destinations. It is based on a survey questionnaire proposed to adultsprimarily in Germany, USA and Sweden. The study demonstrates the intrinsic relationshipbetween the transport mode choices for reaching tourism destinations, and the different levels ofvariables that could cause different types of green mobility decisions made to reach their tourismdestinations.

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<p>Land use planning has gained popularity as a travel demand management strategy for the last two decades. Many urban authorities in North America have adopted smart growth policies in order to curb auto use and promote sustainable forms of travel, namely, public transit, bicycle and walking. The purpose of this study is to examine whether someone’s travel behavior is influenced by the characteristics of the built environment where one lives and works. The study area is Halifax Regional Municipality, Nova Scotia, Canada. Two aspects of travel are analyzed for a weekday: total distance travelled by auto and average tour complexity. Separate models are developed for worker and non-worker by applying ordinary least square and spatial lag modeling techniques. The built environment variables are measured near home and workplace and at different geographical scales. The average auto distance and tour complexity are separately regressed against the built environment variables while personal characteristics, household attributes, preferences for residential location and transport mode, and meteorological conditions of survey days are accounted for. The results of auto distance models suggest that people living and working in high accessibility areas with mixed land uses make shorter travel by auto, which supports the claims of smart growth proponents. The built environment variables make significant contribution to the fitness of auto distance models. In case of tour complexity models, built environment variables also appear to be significant but with lower contribution to model <em>R²</em>. The results suggest that non-workers, who live in poor accessibility areas, make more complex tours. Workers living in poorly accessible neighborhoods and working in highly accessible areas make complex commuting and work-based, non-work tours. It means that, workers compensate poor neighborhood accessibility by trip chaining near workplace. The findings would be helpful to evaluate the existing growth strategies in Halifax Regional Municipality. In addition, it makes several contributions to the literature.</p> / Master of Arts (MA)

Public bike share systems have been recognized as an effective way to promote active and sustainable public transportation. With the health benefits of bike share becoming better understood, North American cities have continued to invest in cycling infrastructure and impose new policies to not only encourage the usage of bike share systems but also expand their operations to new cities. The city of Hamilton, Ontario, implemented its own bike share system in March 2015. Using the system’s global positioning system (GPS) data for annually aggregated trip departures, arrivals, and totals in 2017, this research explores various environment factors that have an impact on users’ bike share usage at hub level. Nine predictive linear regression models were developed for three different scenarios depending on the type of hubs and members for trip departures, arrivals, and totals. In terms of variance explained across the core service area, the models suggested the main factors that attract users were distance to McMaster University and the number of racks available at hubs. Furthermore, the working population and distance to the Central Business District and the closest bike lane in the immediate vicinity (200 m buffer) also played important roles as contributing factors. Based on the primary predictors, this research takes one step further and estimates potential trips at candidate sites to inform future expansion of public bike share system. The candidate locations were created on appropriate land uses by applying a continuous surface of regularly shaped cells, a hexagonal tessellation, on the area of interest. The estimated potential usage at candidate sites demonstrated that the east part of the city should be targeted for future bike share expansion. / Dissertation / Master of Science (MSc)

This dissertation employs a mixed methods research design to examine the travel behavior of immigrants (individuals with an immigration background) in Vienna, Austria. Almost half of the city´s population has an immigration background. This study aims to understand the motivations, perceptions and attitudes influencing the travel behavior of individuals with an immigration background. The two main dependent variables in the analysis throughout the dissertation are mode choice and the satisfaction with six aspects of public transit: costs, travel time, equipment, connectivity, waiting times and safety. The first part of the dissertation will present a quantitative analysis of two datasets, one provided by Statistik Austria, and one self-conducted survey, in which overall trends and predicting factors of travel behavior in Vienna will be presented. The second part of the dissertation offers a qualitative view on travel behavior. 21 semi-structured interviews have been conducted with individuals with and without an immigration background to further the understanding of the underlying factors leading to their travel behavior. The quantitative analysis has shown that individuals with an immigration background from Turkey or former Yugoslavia in general drive more and ride public transit less than individuals without an immigration background. This effect is especially prevalent for work-trips. Individuals with an immigration background from Turkey or former Yugoslavia are also less satisfied with the majority of the six aspects of public transit. The interviews have shown that the rationale between driving more for individuals with an immigration background from Turkey or former Yugoslavia do not stem from transportation or land-use related factors, but rather from political attitudes and viewing the car as a status symbol. Policies set out by the government, such as introducing a cheap annual pass compared with most other cities, are seen negatively as a push to make people give up their cars and use public transit exclusively. The interviews have also found that perceptions of public transit for individuals with an immigration background are greatly influenced by previous experiences regarding public transit in other countries. This dissertation fills a methodological and substantial gap. First, it employs mixed-methods research design using phenomenology in the qualitative analysis to capture the experiences of the interview participants in an accurate way. Substantially, this research has shown, that policies which aim at incentivizing individuals to switch to public transit by offering affordable annual passes do not reach some individuals with an immigration background due to government skepticism. Cities employing transportation policies should not view transportation as a mere technical realm, but rather as a construct filled with social, cultural, and economic aspects. / Doctor of Philosophy / Most large cities in the world have large immigrant populations. However, there is not much scholarly research on how these people travel within these cities in daily life. Additionally, the perceptions of immigrants and non-immigrants regarding public transit will be examined. In this dissertation, there will be four main research topics. First, through statistical analysis, the differences of travelling within the city between immigrants and non-immigrants is analyzed. Second, the reasons and motivations behind these travel patterns will be investigated through interviews with immigrants and non-immigrants. Third, the differences in the perceptions of public transit between immigrants and non-immigrants will be understood. Finally, the underlying reasons behind the perceptions of public transit will be investigated. In this study, I am using statistical analysis as well as interviews to address the four research topics. The statistical analysis has shown that Turkish or former Yugoslavian immigrants are more likely to drive regularly, particularly when travelling for work-related purposes, compared to non-immigrants. The interviews have showed that the reason behind this travel behavior lies in a skeptical attitude towards public transit, which has primarily political reasons. Additionally, these immigrants see the car as a high-status symbol representing economic success

This dissertation seeks to understand travel satisfaction, travel affinity, and other psychological factors in relation to travel demand, such as the desire for trip making, willingness to spend time traveling, and choice of travel mode. The research was based on the Mood State in Transport Environments survey of 247 Android users (about 6,000 completed trip surveys) in the Blacksburg-Roanoke, VA, Washington, DC, and Minneapolis, MN metropolitan areas from fall 2016 to spring 2018. Respondents answered an entry survey, tracked their travel for 7 days, and answered a trip survey associated with each trip. The dataset provides opportunities to examine travel and activities during travel at the within- and between-person levels. Three studies in this dissertation examined three measures of the positive utility of travel and their relationship with travel behavior. I quantified (1) the desirability of trip making, (2) the ideal travel time related to different travel characteristics, and (3) the effect of satisfaction on commute mode choice. The first study examines the patterns of travel affinity with various travel modes, trip purposes, and activities during the trip. Travel affinity was measured by asking the willingness to forgo a trip when there is an opportunity to do so. I found that this is a valid and strong measure of the positive utility of travel. Travelers were more willing to make trips when they traveled on foot or bicycle, talked with someone during the trip, and took shorter trips. Additionally, commute trips were less likely to be enjoyed as compared to other, non-commute trips. The second study focused on (1) testing the validity of the "ideal travel time" measurement and (2) measuring factors associated with the willingness to spend time traveling. I found that although ideal travel time was a strong measure of the positive utility of travel, it was very weakly associated with the desirability of trip making and satisfaction with trips. Although few people wanted zero commute time (3%), the number of trips that had zero ideal travel time was much higher (16%), indicating that the desired travel amount may vary across different trip and environmental characteristics and purpose. Ideal travel time was longer for active travel trips, leisure trips, when conducting activities during trips (e.g., talking, using the phone, looking at the landscape), when traveling with companions and during the weekend. The third study investigated the role of travel satisfaction and attitude in mode choice behavior. This is one of the very few studies that have considered the role of these psychological factors in multimodal mode choice based on revealed preference data. I found that satisfaction and attitude toward modes and travel played a significant role in the choice model; it also modified the role of travel time in the models. However, the perception of travel time usefulness was insignificant in the model. Scenario analyses based on the model results showed that it is optimal to invest in active transportation and public transit at the same time in order to shift car drivers to these sustainable modes. These studies contribute to the small but growing body of literature on the positive utility of travel and transrational decision making in transportation. It is the only study that employed a smartphone survey with a repeated measure of trips over the course of 1-2 weeks. The third study is among the earliest attempts to include satisfaction and attitude together into mode choice models. This dissertation has several implications for research and practice. First, it calls for better measurements of well-being and satisfaction. Second, models with appropriate psychological factors would more realistically resemble actual travel behavior. Including satisfaction in the choice model changes the coefficient of travel time (and potentially cost), which modifies the value of travel time savings, a basis of most benefit-cost analyses in transportation planning and engineering. Better mode choice and trip generation models will generate more reliable predictions of future infrastructure use and investment. Third, studies of travel affinity (positive utility of travel) have implications for demand modeling and management practice. Practitioners should reevaluate the effectiveness of travel demand management strategies aimed at reducing travel time and trips, such as congestion pricing (e.g., tolls), online shopping, and telecommuting. / Doctor of Philosophy / People have various motivations to travel every day. For some, traveling is a means to an end to get from one place to another. Their main travel purpose is to perform some activities at destinations, such as grocery shopping, working, or visiting a friend. For others, traveling is a joy to get some fresh air, to be on one’s own company, to enjoy driving or exercising (while walking or bicycling), in addition to conducting activities at destinations. This idea of traveling for fun is still unpopular in transportation research. This dissertation seeks to understand the patterns of travel and motivations: who are traveling for fun, and when? Whether this affinity and satisfaction for travel drive people’s decision to choose a travel mode? To answer these questions, I measured the affinity for travel in two ways: willingness to make trips (i.e., travel from one place to another) and desired amount of time spent on travel. I found that people were willing to travel more when they conducted certain activities during trips, such as talking to others, talking on the phone, or other activities. Commuting was less fun as compared to other travel purposes, such as socializing or leisure. Bicyclists and pedestrians liked their trips and wanted to travel more than car drivers and bus users. People who were satisfied with their commute trips made by one mode would be more likely to use that mode for commuting. The affinity for travel is relevant to urban residents’ mental well-being and demand for travel, which translate into health and congestion relief benefits. The results from my studies suggest that more attentions on traveling for fun and multitasking should be paid to account for future mobility options, such as ride hailing (e.g., Uber, Lyft) and autonomous vehicles. These modes have promised fun from activities during travel, the autonomy, and convenience, and thus would generate more traffic on the road while providing less social and environmental benefits. The results from this dissertation would inform city planners, engineers, and health practitioners on planning for sustainable cities by improving well-being for transportation users and accommodate sustainable modes of transport, such as bicycling, walking, and transit by providing users with safe and satisfactory travel environments. The results also imply potential pitfalls of the current planning practice such as overestimating the value of travel time savings, benefit-cost analyses, and the effectiveness of travel demand management strategies, such as telecommuting and using information and communications, in reducing travel.

Indian cities have been witnessing rapid transformation due to the synergistic effect of industrialisation, flourishing-economy, motorisation, population explosion, and migration. The alarming increase in travel demand as an after effect of the transformation, and the scarcity in transport infrastructures have exacerbated urban transport issues such as congestion, pollution, and inequity. Due to the escalating cost of transport infrastructure and the scarcity of resources such as space, there has been an increasing interest in promoting sustainable transportation policy measures for the optimum use of existing resources. Such policy measures mostly target the activitytravel behaviour of individuals to bring about desired changes in the transport sector. However, the responses of individuals to most of the measures are complex or unknown. The current ‘commute trip-based’ aggregate travel demand analysis strategy followed in most of the Indian cities is inadequate for providing basic inputs to understand the activity-travel behaviour of individuals under such policy interventions. Furthermore, the current analysis strategy also ignores the activitytravel behaviour of non-workers – who include homemakers, unemployed, and retired individuals – whose inclusion to transportation planning is relevant when the proposed policies are mostly ‘citizen-centric’. Analysis of activity-travel behaviour of non-workers provide important inputs to transportation planning as their activity-travel behaviour, and responses to transportation policies are different from that of workers. However, case studies exploring the activity-travel behaviour of non-workers from Indian cities are very limited. Appraising the practical importance of this subject, the current research undertakes a comprehensive analysis of the activity-travel behaviour of non-workers from a developing country’s context. To fulfil the goal, a series of empirical analysis are conducted on a primary activity-travel weekday survey data collected from Bangalore city. The analysis provides insightful findings and interpretations consistent with a developing country’s perspective. The day-planner format of time use diary, which was observed to have satisfactory performances in developed countries, is apparently have inferior performances in a developing country’s context. Further, the face-to-face method of survey administration is observed to have higher operating and economic efficiencies compared to the drop-off and pick-up method. The comprehensive analysis of activity-travel behaviour of non-workers indicate that comparing with their counterparts in the developed world (e.g. the U.S.), non-workers in Bangalore city are observed to have lower activity participation level (in terms of time allocation and number of stops), higher dependency on walking, lower trip chaining tendency, and a distinct time-of-day preference for departing to activity locations. On the other hand, the analysis shows similarities (mode use and trip chaining) and differences (time allocation and departure time choice) with the findings of the case studies from the developing world (e.g. China). Activity-travel behaviour of non-workers belonging to low-income households is characterised by lower activity participation level, higher dependency on sustainable transport modes, and lower trip chaining propensity, compared to other two income groups (middle and high-income groups). The research also suggests that built environment measures have their highest impacts on non-workers’ travel decisions related to shopping. Finally, the joint analysis of activity participation and travel behaviour of non-workers indicate that in-home maintenance activity duration drives the time allocation and travel behaviour of non-workers, and non-workers trade in-home discretionary activity duration with travel time. The joint analysis also shows that the time spent on children’s and elders’ activity is an important time allocation of its own. Keywords: Activity-travel behaviour, Non-worker, Time Use, Income Groups, India

This research contributes to a very active body of literature on the application of Automated Data Collection Systems (ADCS) and openly shared data to public transportation planning. It also addresses the interaction between transit demand and land use patterns, a key component of generating time-varying origin-destination (O-D) matrices at a route level. An origin-destination (O-D) matrix describes the travel demand between two different locations and is indispensable information for most transportation applications, from strategic planning to traffic control and management. A transit passenger's O-D pair at the route level simply indicates the origin and destination stop along the considered route. Observing existing land use types (e.g., residential, commercial, institutional) within the catchment area of each stop can help in identifying existing transit demand at any given time or over time. The proposed research addresses incorporation of an alighting probability matrix (APM) - tabulating the probabilities that a passenger alights at stops downstream of the boarding at a specified stop - into a time-varying O-D estimation process, based on the passenger's trip purpose or activity locations represented by the interactions between transit demand and land use patterns. In order to examine these interactions, this research also uses a much larger dataset that has been automatically collected from various electronic technologies: Automated Fare Collection (AFC) systems and Automated Passenger Counter (APC) systems, in conjunction with other readily available data such as Google's General Transit Feed Specification (GTFS) and parcel-level land use data. The large and highly detailed datasets have the capability of rectifying limitations of manual data collection (e.g., on-board survey) as well as enhancing any existing decision-making tools. This research proposes use of Google's GTFS for a bus stop aggregation model (SAM) based on distance between individual stops, textual similarity, and common service areas. By measuring land use types within a specified service area based on SAM, this research helps in advancing our understanding of transit demand in the vicinity of bus stops. In addition, a systematic matching technique for aggregating stops (SAM) allows us to analyze the symmetry of boarding and alightings, which can observe a considerable passenger flow between specific time periods and symmetry by time period pairs (e.g., between AM and PM peaks) on an individual day. This research explores the potential generation of a time-varying O-D matrix from APC data, in conjunction with integrated land use and transportation models. This research aims at incorporating all valuable information - the time-varying alighting probability matrix (TAPM) that represents on-board passengers' trip purpose - into the O-D estimation process. A practical application is based on APC data on a specific transit route in the Minneapolis - St. Paul metropolitan area. This research can also provide other practical implications. It can help transit agencies and policy makers to develop decision-making tools to support transit planning, using improved databases with transit-related ADCS and parcel-level land use data. As a result, this work not only has direct implications for the design and operation of future urban public transport systems (e.g., more precise bus scheduling, improve service to public transport users), but also for urban planning (e.g., for transit oriented urban development) and travel forecasting.

Long-distance and intercity travel generally make up a small portion of the total number of trips taken by an individual, while representing a large portion of aggregate distance traveled on the transportation system. While some research exists on intercity travel behavior between large metropolitan centers, this thesis addresses a need for more research on travel behavior between non-metropolitan areas and large metropolitan centers. This research specifically considers travel from home locations in northern New England, going to Boston, New York City, Philadelphia, and Washington, DC. These trips are important for quality of life, multimodal planning, and rural economies. This research identifies and quantifies factors that influence people's mode choice (automobile, intercity bus, passenger rail, or commercial air travel) for these trips. The research uses survey questionnaire data, latent factor analysis, and discrete choice modeling methods. Factors include sociodemographic, built environment, latent attitudes, and trip characteristics. The survey, designed by the University of Vermont Transportation Research Center and the New England Transportation Institute, was conducted by Resource Systems Group, Inc. in 2014, with an initial sample size of 2560. Factor analysis was used to prepare 6 latent attitudinal factors, based on 70 attitudinal responses from the survey statements. The survey data were augmented with built environment variables using geographic information systems (GIS) analysis. A set of multinomial logit models, and a set of nested logit models, were estimated for business and non-business trip mode choice. Results indicate that for this type of travel, factors influencing mode choice for both business and non-business trips include trip distance; land use; personal use of technology; and latent attitudes about auto dependence, preference for automobile, and comfort with personal space and safety on public transportation. Gender is a less significant factor. Age is only significant for non-business trips. The results reinforce the importance and viability of modeling long-distance travel from less populated regions to large metropolitan areas, and the significant roles of trip distance, built environment, personal attitudes, and sociodemographic factors in how people choose to make these trips for different purposes. Future research should continue to improve these types of long-distance mode choice models by incorporating mode specific travel time and cost, developing more specific attitudinal statements to expand latent factor analysis, and further exploring built environment variables. Improving these models will promote better planning, engineering, operations, and infrastructure investment decisions in many regions and communities across the United States which have not yet been well studied, possibly impacting levels of service.