Corruption as a field of economics: Experimental approach and design

OBJECTIVES OF THE STUDY: This thesis has three main objectives. To provide a thorough review of the theoretical foundation of corruption in economics, introduce the methodologies and their main results and lastly design an economic corruption experiment addressing mechanics and importance of reciprocity for individuals in comparison to other moral costs of corruption. THEORETICAL FOUNDATION: Theoretical foundation reviewed in the thesis comprises of both theoretical and practical aspects of corruption. Theoretical part includes definitions and main categories of corruption while the practical part introduces the real world mechanics of corruption and the challenge they pose for development of a unified theory of corruption and anticorruption policies. METHODOLOGIES: While this thesis introduces all five main approaches to corruption research in economics; perception indices, surveys, observation and lab and field experiments, special emphasis is placed on the latter two that comprise the experimental approaches of corruption research. The experimental approach is shown to have revolutionized an otherwise stagnant field of economics and holds great promise as a research tool for the notoriously difficult research subject of corruption. EXPERIMENTAL DESIGN: This thesis provides a complete design, motivation and theoretical foundation for an experiment of the corrupting effects of reciprocity in bribery. As reciprocity is identified to be the key mechanic of bribery, this experiment intends to examine and value the effects of reciprocity on individual's decision making as a source of implicit bribery

Dynamic-Occlusion-Aware Risk Identification for Autonomous Vehicles Using Hypergames

A particular challenge for both autonomous vehicles (AV) and human drivers is dealing with risk associated with dynamic occlusion, i.e., occlusion caused by other vehicles in traffic. In order to overcome this challenge, we use the theory of hypergames to develop a novel dynamic-occlusion risk measure (DOR). We use DOR to evaluate the safety of strategic planners, a type of AV behaviour planner that reasons over the assumptions other road users have of each other. We also present a method for augmenting naturalistic driving data to artificially generate occlusion situations. Combining our risk identification and occlusion generation methods, we are able to discover occlusion-caused collisions (OCC), which rarely occur in naturalistic driving data. Using our method we are able to increase the number of dynamic-occlusion situations in naturalistic data by a factor of 70, which allows us to increase the number of OCCs we can discover in naturalistic data by a factor of 40. We show that the generated OCCs are realistic and cover a diverse range of configurations. We then characterize the nature of OCCs at intersections by presenting an OCC taxonomy, which categorizes OCCs based on if they are left-turning or right-turning situations, and if they are reveal or tagging-on situations. Finally, in order to analyze the impact of collisions, we perform a severity analysis, where we find that the majority of OCCs result in high-impact collisions, demonstrating the need to evaluate AVs under occlusion situations before they can be released for commercial use

Smart Sustainable Mobility: Analytics and Algorithms for Next-Generation Mobility Systems

To this date, mobility ecosystems around the world operate on an uncoordinated, inefficient and unsustainable basis. Yet, many technology-enabled solutions that have the potential to remedy these societal negatives are already at our disposal or just around the corner. Innovations in vehicle technology, IoT devices, mobile connectivity and AI-powered information systems are expected to bring about a mobility system that is connected, autonomous, shared and electric (CASE). In order to fully leverage the sustainability opportunities afforded by CASE, system-level coordination and management approaches are needed. This Thesis sets out an agenda for Information Systems research to shape the future of CASE mobility through data, analytics and algorithms (Chapter 1). Drawing on causal inference, (spatial) machine learning, mathematical programming and reinforcement learning, three concrete contributions toward this agenda are developed. Chapter 2 demonstrates the potential of pervasive and inexpensive sensor technology for policy analysis. Connected sensing devices have significantly reduced the cost and complexity of acquiring high-resolution, high-frequency data in the physical world. This affords researchers the opportunity to track temporal and spatial patterns of offline phenomena. Drawing on a case from the bikesharing sector, we demonstrate how geo-tagged IoT data streams can be used for tracing out highly localized causal effects of large-scale mobility policy interventions while offering actionable insights for policy makers and practitioners. Chapter 3 sets out a solution approach to a novel decision problem faced by operators of shared mobility fleets: allocating vehicle inventory optimally across a network when competition is present. The proposed three-stage model combines real-time data analytics, machine learning and mixed integer non-linear programming into an integrated framework. It provides operational decision support for fleet managers in contested shared mobility markets by generating optimal vehicle re-positioning schedules in real time. Chapter 4 proposes a method for leveraging data-driven digital twin (DT) frameworks for large multi-stage stochastic design problems. Such problem classes are notoriously difficult to solve with traditional stochastic optimization. Drawing on the case of Electric Vehicle Charging Hubs (EVCHs), we show how high-fidelity, data-driven DT simulation environments fused with reinforcement learning (DT-RL) can achieve (close-to) arbitrary scalability and high modeling flexibility. In benchmark experiments we demonstrate that DT-RL-derived designs result in superior cost and service-level performance under real-world operating conditions

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions

Why should you read another book about transport and land use? This book differs in that we won’t focus on empirical arguments – we present political arguments. We argue the political aspects of transport policy shouldn’t be assumed away or treated as a nuisance. Political choices are the core reasons our cities look and function the way they do. There is no original sin that we can undo that will lead to utopian visions of urban life. The book begins by introducing and expanding on the idea of Accessibility. Then we proceed through several major parts: Infrastructure Preservation, Network Expansion, Cities, and Institutions. Infrastructure preservation concerns the relatively short-run issues of how to maintain and operate the existing surface transport system (roads and transit). Network expansion in contrast is a long-run problem, how to enlarge the network, or rather, why enlarging the network is now so difficult. Cities examines how we organize, regulate, and expand our cities to address the failures of transport policy, and falls into the time-frame of the very long-run, as property rights and land uses are often stickier than the concrete of the network is durable. In the part on Institutions we consider things that might at first blush appear to be short-run and malleable, are in fact very long-run. Institutions seem to outlast the infrastructure they manage. Many of the transport and land use problems we want to solve already have technical solutions. What these problems don’t have, and what we hope to contribute, are political solutions. We expect the audience for this book to be practitioners, planners, engineers, advocates, urbanists, students of transport, and fellow academics

THE CONSTRUCTION OF LOCAL ROAD SAFETY ISSUES: WHEN LAY AND PROFESSIONAL DISCOURSES COLLIDE

Highway Authorities in the United Kingdom have jurisdiction to control, maintain and improve the local highway network, and the Road Traffic Act 1988 places a duty on such authorities to take preventative measures to reduce road casualties. As such, engineers working for the Highway Authority are on the ‘front-line,’ and are required to deal directly with lay concerns relating to road safety. This study investigates the nature and characteristics of how local road safety issues are raised and how engineers respond to such issues in a local authority setting. A grounded theory methodology was applied in the collection and analysis of this data, and in the generation of subsequent emergent themes. Datasets were established containing textual data from correspondence between the lay public and the authority, and from local press reporting. This was augmented by 47 semi-structured interviews with engineers. The analysis demonstrates that road safety issues and their construction, form a distinct genre. There are certain characteristic structural elements and argumentative approaches, which are oft repeated, in lay formulations of road safety. Road safety issues are played out in a contested field, although engineers may have, in theory, the ‘expertise’ that grants them authority to assess, diagnose and implement mitigation measures; in practice they have little autonomy or control. Regulatory restrictions, political interference, resource impoverishment and a volatile public, severely limit engineers’ independence and discretion. In dealing with the exigencies and pressures of day-to-day front-line public service, engineers deploy certain strategies for ‘managing’ the public. These pragmatic strategies are examined in order to establish how engineers can best effect practical action, in the face of competing and often conflicting demands. In examining the rhetorical organisation of lay argumentative strategies, a ‘popular epidemiology’ of road safety is recreated. This term, borrowed from Brown (1992), encapsulates a folk philosophy with respect to accident causation and the measures that are considered necessary or appropriate to ameliorate/eliminate identified issues. It is suggested that in vivo formulations of road safety issues, such as the ‘accident waiting to happen’ are founded on vague premises, and constitute a category mistake. Projections from phenomenally troubling, yet largely unsubstantiable events, to those with profound material consequences, are neither necessary nor certain. In making decisions on substantial capital investments, engineers, by necessity, are required to assess competing sites on a more epistemically secure metric, namely the police road casualty record

Unauthorized Access

Going beyond current books on privacy and security, this book proposes specific solutions to public policy issues pertaining to online privacy and security. Requiring no technical or legal expertise, it provides a practical framework to address ethical and legal issues. The authors explore the well-established connection between social norms, privacy, security, and technological structure. They also discuss how rapid technological developments have created novel situations that lack relevant norms and present ways to develop these norms for protecting informational privacy and ensuring sufficient information security

Considering stakeholders’ preferences for scheduling slots in capacity constrained airports

Airport slot scheduling has attracted the attention of researchers as a capacity management tool at congested airports. Recent research work has employed multi-objective approaches for scheduling slots at coordinated airports. However, the central question on how to select a commonly accepted airport schedule remains. The various participating stakeholders may have multiple and sometimes conflicting objectives stemming from their decision-making needs. This complex decision environment renders the identification of a commonly accepted solution rather difficult. In this presentation, we propose a multi-criteria decision-making technique that incorporates the priorities and preferences of the stakeholders in order to determine the best compromise solution

Testing automated driving systems to calibrate drivers’ trust

Automated Driving Systems (ADSs) offer many potential benefits like improved safety, reduced traffic congestion and lower emissions. However, such benefits can only be realised if drivers trust and make use of such systems. The two challenges explored in this thesis are: 1) How to increase trust in ADSs? 2) How to identify the test scenarios to establish the true capabilities and limitations of ADSs? Firstly, drivers’ trust needs to be calibrated to the “appropriate” level to prevent misuse (due to over trust) or disuse (due to under trust) of the system. In this research, a method to calibrate drivers’ trust to the appropriate level has been created. This method involves providing knowledge of the capabilities and limitations of the ADSs to the driver. However, there is a need to establish the capabilities and limitations of the ADSs which form the knowledge to be imparted to the driver. Therefore, the next research contribution lies in the development of a novel method to establish the knowledge of capabilities and limitations of ADSs (used to calibrate trust) in a reliable manner. This knowledge can be created by testing ADSs. However, in literature, an unanswered research question remains: How to identify test scenarios which highlight the limitations of ADSs? In order to identify such test scenarios, a novel hazard based testing approach to establish the capabilities and limitations of ADSs is presented by extending STPA (a hazard identification method) to create test scenarios. To ensure reliability of the hazard classification (and of the knowledge), the author created a novel objective approach for risk classification by creating a rule-set for risk ratings. The contribution of this research lies in developing a method to increase trust in ADSs by creating reliable knowledge using hazard based testing approach which identifies how an ADS can fail

License to Supervise:Influence of Driving Automation on Driver Licensing

To use highly automated vehicles while a driver remains responsible for safe driving, places new – yet demanding, requirements on the human operator. This is because the automation creates a gap between drivers’ responsibility and the human capabilities to take responsibility, especially for unexpected or time-critical transitions of control. This gap is not being addressed by current practises of driver licensing. Based on literature review, this research collects drivers’ requirements to enable safe transitions in control attuned to human capabilities. This knowledge is intended to help system developers and authorities to identify the requirements on human operators to (re)take responsibility for safe driving after automation