1,863 research outputs found

    Cycling Through the Pandemic : Tactical Urbanism and the Implementation of Pop-Up Bike Lanes in the Time of COVID-19

    Get PDF
    Provides an international overview on how tactical urbanism was implemented to give more space to cycling Demonstrates the conceptual framework surrounding tactical urbanism and how it plays out theoretically Proposes new methodological insights to understand the effects of tactical urbanism intervention

    Who watches the watchmen? Assessing potential regulatory capture through an examination of historical Surface Transportation Board (STB) decisions on shipper/railroad disputes

    Get PDF
    This thesis will examine a series of historical decisions made by a major U.S. regulatory body, the Surface Transportation Board (STB) in the surface freight transportation sector. As a federal regulator overseeing a major industry, the STB (and the ICC before it) were created to operate as a neutral economic regulator acting in the public interest, managing relationships and disputes between surface railroads (in this case, railroads) and their shipper customers. But understanding the incentives and consequences described by Stigler (1971) in the context of economic regulation and capture, in particular the U.S. freight rail sector continues to operate under some controversy because of the questionable regulatory objectivity of the STB as the railroad regulator (Gallamore, 2014). Much of the prior regulatory research about the STB has focused on its scope along with key issues resulting from the agency’s long term regulation of the rail sector (Goldman, 2022), as well as the impact of regulation on the operation and management of the U.S. freight rail system. Other related literature tries to gain insight on decision processes as well as rationalizing the outcomes of the STB decisions over various freight disputes (Warren, 2018). But in spite of this body of research, to our knowledge there have been few if any analytic attempts to assess the fairness or objectivity of the STB regulatory decisionmaking. One interesting feature of the STB crucial to our assessment is that the agency maintains an online compendium or database of its decisions, going back well into the 1990’s and overall numbering into the thousands. As a qualitative database it can be difficult to use for analytics, but it is detailed and allows us to set up both empirical and qualitative assessments of regulatory objectivity. A further underlying factor in formulating this thesis was the effort required to identify and code the sub-set of relevant STB decisions that were both thematically consistent (i.e. rate disputes between a railway and a shipper) as well as independent over time to the present. This extensive vetting yielded individual decisions/data points that were used to conduct our initial statistical analysis and subsequent qualitative work. After reviewing related literature on assessments of regulatory objectivity in other industries, the empirical part of the thesis estimates various statistical tests (randomness tests, tests of distributional differences) on the case decision data to identify whether or not the data were generated by a neutral decision-maker. To supplement the statistical analysis and to help facilitate understanding of the reasonability and justifiability of STB decisions, we further qualitatively analyze the same cases to add insight on regulatory behavior. Overall, we hope this study will contribute to a better understanding about the decision-making process of a major U.S. economic regulator. Further, we hope this work might help improve STB performance by improving future objectivity in regulatory decision-making within the US freight rail sector

    Short Run Transit Route Planning Decision Support System Using a Deep Learning-Based Weighted Graph

    Full text link
    Public transport routing plays a crucial role in transit network design, ensuring a satisfactory level of service for passengers. However, current routing solutions rely on traditional operational research heuristics, which can be time-consuming to implement and lack the ability to provide quick solutions. Here, we propose a novel deep learning-based methodology for a decision support system that enables public transport (PT) planners to identify short-term route improvements rapidly. By seamlessly adjusting specific sections of routes between two stops during specific times of the day, our method effectively reduces times and enhances PT services. Leveraging diverse data sources such as GTFS and smart card data, we extract features and model the transportation network as a directed graph. Using self-supervision, we train a deep learning model for predicting lateness values for road segments. These lateness values are then utilized as edge weights in the transportation graph, enabling efficient path searching. Through evaluating the method on Tel Aviv, we are able to reduce times on more than 9\% of the routes. The improved routes included both intraurban and suburban routes showcasing a fact highlighting the model's versatility. The findings emphasize the potential of our data-driven decision support system to enhance public transport and city logistics, promoting greater efficiency and reliability in PT services

    The Mogadishu Effect: America\u27s Failure-Driven Foreign Policy

    Get PDF
    The October 1993 Battle of Mogadishu, commonly referred to as “Black Hawk Down,” transformed American foreign policy in its wake. One of the largest special operations missions in recent history, the failures in Somalia left not only the United States government and military in shock, but also the American people. After the nation’s most elite fighting forces suffered a nearly 50 percent casualty rate at the hands of Somali warlords during what many Americans thought was a humanitarian operation, Congress and the American people erupted in anger. Although the United States has continued to be seen as an overbearing global peacekeeping force in the thirty years since Somalia, the Battle of Mogadishu served as the turning point for a generational foreign policy shift that significantly limited future global intervention because of the overt publicization of battle’s aftermath in the media, domestic and international reactions, and a fear of repeating the same mistakes elsewhere. The first major American loss of life after the Cold War, the battle and the reaction that followed, known as the “Mogadishu effect,” forced President Clinton to rethink the United States’ role internationally. Clinton and his administration struggled to convince the American people that involvement overseas, especially global peacekeeping, was vital to international order after becoming the world’s sole superpower. Congressional hearings, presidential correspondence, government documents, poll results, and numerous media releases across Clinton’s presidency mark the distinct shift in American foreign policy that took place after Mogadishu. Although he inherited involvement in the United Nations mission in Somalia from George H.W. Bush, the failures in Somalia transformed Clinton’s humanitarian involvement in Haiti, Bosnia, and Rwanda, tarnishing the remainder of his presidency and shifting expectations of significant American involvement in international peacekeeping after the Cold War

    Current issues of the management of socio-economic systems in terms of globalization challenges

    Get PDF
    The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges

    Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

    Get PDF
    Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

    USA Rail Planner: A user-focused web-scraping solution for rail travel planning in the United States

    Get PDF
    Planning a cross-country train journey in the United States can be a time-consuming process. The USA Rail Planner, presented in this thesis, provides travelers an easy way to plan a multi-city rail trip to any of the destinations served by Amtrak trains in the United States. The manual work of searching the Amtrak website and inputting information into a spreadsheet is no longer necessary. By interfacing with the website, information can be parsed by the application quickly and presented to the user in a simpler, ordered, and less cluttered format, allowing them to make educated decisions in their trip planning process. Dynamic route maps, detailed train information, and many other planning features are present in the application. Quality-of-life additions, such as train timetables, city tourism pages, and local transit connections, make the application well-rounded in the tourism and travel domains. Furthermore, this user-centered Python-based application that employs web scraping and other modern software technologies provides an efficient and easy way to create an itinerary which can be exported later. User study results (N=12) show that the USA Rail Planner is significantly better than existing methods, reducing the time to create an itinerary by 47% and it was the preferred method for all but one participant

    Summer 2023 Full Issue

    Get PDF
    corecore