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

As opposed to public transit agencies' well-developed data generation capabilities, their utilization of their data is often overlooked. This study will tap into the potential of using the GTFS data format from an agency stakeholder perspective to assess transit performance. This format holds data for scheduled transit services, including real-time updates and network organization. The broad adaptation of GTFS by transit agencies (1240 transit networks in 672 locations worldwide) has made it a de-facto standard, making products built on top of it inherently scalable and could potentially be deployed in networks all over the world. The purpose of this thesis is two-fold; firstly, to explore how specific vulnerability features of nodes in a public transit network can be assessed using graph mining algorithms. Secondly, to develop a pipeline for aggregating GTFS data and fit it into a flow network model. The results include a data-driven framework for vulnerability characterization, a method for fitting GTFS data in a flow network model, and lastly, a definition for reduced flow capacity in a public transit context. Additionally, the results are presented in the setting of Uppsala's network (UL) and visualized with a web-based tool.

Public transit is becoming an increasing important field of study to combat global issues such as traffic congestion and climate change. Accurate simulation of public transit is therefore likewise vital, as it is an important tool for understanding potential impacts of public transit policies. The research presented in this thesis describes the implementation of a multimodal, dynamic, agent-based supply-side simulation model of public transit implemented in the open-source platform MATSim for the city of Toronto. Transit schedule data was converted from Google Transit Feed Specification (GTFS) and map-matched to a region-wide road network to obtain a congestion-based multimodal assignment for transit. Volume-based results from the assignment showed under-prediction of subway volumes and slight over-prediction of bus volumes, but were generally comparable with static EMME/3 assignment for the same data. Travel time analysis indicated that further calibration of network specification is needed.

Public transit is becoming an increasing important field of study to combat global issues such as traffic congestion and climate change. Accurate simulation of public transit is therefore likewise vital, as it is an important tool for understanding potential impacts of public transit policies. The research presented in this thesis describes the implementation of a multimodal, dynamic, agent-based supply-side simulation model of public transit implemented in the open-source platform MATSim for the city of Toronto. Transit schedule data was converted from Google Transit Feed Specification (GTFS) and map-matched to a region-wide road network to obtain a congestion-based multimodal assignment for transit. Volume-based results from the assignment showed under-prediction of subway volumes and slight over-prediction of bus volumes, but were generally comparable with static EMME/3 assignment for the same data. Travel time analysis indicated that further calibration of network specification is needed.

The theorethical part contains a description of city public transit, its importance and history, priorities used in city public transit, tariff system, integrated transport systems and vehicles used in city public transit. The public transit systems in both cities are introduced and compared from several points of view in the practical part. The cities compared are Prague and San Francisco.

An expansion of the railway, East Coast Line is essential in order to ensure transportation of passenger and goods back and forth to Northern Sweden. The preliminary studies of the planned expansion to a double track have identified vulnerabilities linked to how our climate changes. Because of these risks and vulnerabilities, the railway station in Hudiksvall needs to be relocated or the Current station needs to be adapted to potential future climate scenarios. Furthermore, social sustainability and the aspect of accessibility is also a vital perspective to consider during the development of railway infrastructure. This study compares the three different station locations from an accessibility perspective and from different climate scenarios through Network Analyst in ArcGIS Pro. To visualize future climate scenarios, two RCP-scenarios (Representative Concentration Pathways) are considered, which is RCP 4.5 and RCP8.5. Additionally, the GTFS specification in ArcGIS Pro is used to model public transit to these railway stations in an accessibility perspective. Because one strategy when developing the East Coast Line is to increase the active transportation in comparison to car transportation.  Results from this study indicates that the Current station, which is located in a coastal area will be worst affected of potential future climate scenarios from an accessibility perspective. Other findings are that vulnerable groups in the society, such as low-income earners and elderly will be most affected, if the railway station remains in the current location. The results from the performed Service area analysis and Location-allocation analysis advocates the Eastern station as a location for the new railway station. / En expansion av Ostkustbanan är viktigt för att kunna säkerställa transport av passagerare och gods till och från norra Sverige. Förstudierna av den planerade expansionen till ett dubbelspår har identifierat sårbarheter kopplat till hur vårt klimat förändras. Som en följd av dessa risker och sårbarheter behöver järnvägsstationen i Hudiksvall flyttas. Alternativt behöver den nuvarande klimatanpassas. Detta ställer krav på att ta hänsyn till den sociala hållbarheten och tillgängligheten för befolkningen i Hudiksvall. Denna studie ämnar att jämför de tre olika stationslägena ur ett tillgänglighetsperspektiv samt utifrån olika klimatscenarier i ArcGIS Pro. För att visualisera framtida klimatscenarier beaktas två RCP-scenarier, det vill säga representativa koncentrationsvägar, vilket är RCP4.5 och RCP8.5. Dessutom används GTFS-specifikationen i ArcGIS Pro för att modellera kollektivtrafik till dessa järnvägsstationer ur ett tillgänglighetsperspektiv, då ett mål med utvecklingen av Ostkustbanan är att utöka andelen av personer som väljer aktiv transport i jämförelse med biltransporter.  Resultatet av denna studie visar att den nuvarande stationen, som är placerad i närheten av Hudiksvalls kust, kommer att vara hårdast drabbad av potentiella framtida klimatscenarier ur ett tillgänglighetsperspektiv. Vidare visar studien på att låginkomsttagare och äldre kommer att drabbas hårdast om järnvägsstationen ligger kvar på den nuvarande platsen. Resultatet från de utförda Service area analyserna och Location-allocation analyserna, visar att det östra alternativet är det alternativ som kommer att vara minst påverkad av ett framtida klimat från ett tillgänglighetsperspektiv.

Indiana University-Purdue University Indianapolis (IUPUI) / Food access is a dimension of food security that many struggle with even in high- income countries, which is a contributing factor to chronic diet-related disease. Inequalities in economic access to food has been addressed in public policy for several decades, but spatial access to food has only been seriously studied and addressed by policy for the past twenty-five years. After the food desert metaphor emerged, it was promptly accepted as a standard measure of food access for governments and a basis for policies created to address inequalities. Conceptual criticisms and methodological limitations of the metaphor have led the study of spatial access to food towards newer methods that measure food access more realistically and assist in the development and assessment of intervention strategies to inform policy decisions. This thesis describes the history of the food desert metaphor from its emergence until its adoption in US public policy, the conceptual criticisms and methodological limitations that surround it, and offers an analysis that measures the impact of change in the availability of public transportation on spatial access to food for various population subgroups that are more at risk of food insecurity in Marion County, Indiana. Results demonstrate that policies and plans designed without consideration for food access have an impact on it nevertheless, and that policymakers and planners can leverage such strategies to better coordinate efforts across government to reduce inequalities in spatial access to food and food insecurity overall.

The overarching goal of this dissertation is to examine the spatial, temporal, and modal disparity of access across America. This is achieved by posing three research objectives. The first objective determines the spatial and temporal disparity of transit and automobile access gap, its impact on transit use, and its socioeconomic and built environment correlates. The second objective examines the spatial and temporal disparity of slightly and extremely risky bike infrastructure and measures the social inequity of access to bike infrastructure. The third objective indicates spatial transit access mismatch between high- and low-wage employment across metropolitans. Three findings are discerned. First, the access gap between transit and automobile has a disproportionate effect on African Americans, low-income households, millennials, and car-free households. Second, socially vulnerable communities residing African Americans, Hispanics, and car-free households have the least access to slightly risky bike infrastructure and yet the least prioritized in urban planning and bike infrastructure investments. Third, transit acts as a catalyst to widen spatial mismatch and discriminate socially vulnerable population particularly African Americans and car-free households

Mitigation response plans must be created to protect affected populations during biological emergencies resulting from the release of harmful biochemical substances. Medical countermeasures have been stockpiled by the federal government for such emergencies. However, it is the responsibility of local governments to maintain solid, functional plans to apply these countermeasures to the entire target population within short, mandated time frames. Further, vulnerabilities in the population may serve as barriers preventing certain individuals from participating in mitigation activities. Therefore, functional response plans must be capable of reaching vulnerable populations.Transportation vulnerability results from lack of access to transportation. Transportation vulnerable populations located too far from mitigation resources are at-risk of not being able to participate in mitigation activities. Quantification of these populations requires the development of computational methods to integrate spatial demographic data and transportation resource data from disparate sources into the context of planned mitigation efforts. Research described in this dissertation focuses on quantifying transportation vulnerable populations and maximizing participation in response efforts. Algorithms developed as part of this research are integrated into a computational framework to promote a transition from research and development to deployment and use by biological emergency planners.

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