Blockchain Papers

A. R. Khan

No abstract is available for this record.

GOPICHAND BANDARUPALLI

No abstract is available for this record.

Karlson Hargroves, Peter Newman, Ganesh Raj Joshi, Benjamin James

A dominance of private vehicles in cities around the world has led to unsustainable levels of congestion, pollution, and human harm, which stand to be exacerbated by future growth. This paper briefly outlines the implications of rapid urbanization based on private vehicles and then provides an overview of the benefits associated with Integrated Shared Transit (IST) services. IST can provide a number of benefits such as improved public health outcomes, reduced congestion, and reduced land use from car parking, along with economic development and job creation Opportunities. A recent study suggested this approach presents strong local economic multipliers with every US$1 invested in shared transit creating as much as US$4 in economic returns. The paper then provides a review of four important areas, namely: the shift to electro-mobility, the creation of transit activated corridors (TACs), advanced freight telematics exchange, and the use of disruptive technologies including artificial intelligence and distributed ledgers. The paper then concludes with the recommendation to shift focus from a model of private vehicle dominance to a system of integrated shared transit that is supported by private modes.

Shuchen Zhou, Lei Yu, Yinling Wang, Sami Dhahbi · 6 authors

In this paper, we utilise blockchain technology (BT) and circular q -rung orthopair fuzzy sets ( C q -ROFS) to address practical issues related to urban transportation and supply chain management (SCM). Recognising the weaknesses of earlier approaches such as circular intuitionistic fuzzy sets (C-IFS), we work C q -ROFS to better accommodate imprecise input. Novel approaches that use into metaverse settings are being investigated as a means of addressing the complex problems associated with urban mobility. This study use the SWARA-AROMAN approach to evaluate potential blockchain integration possibilities for metaverse urban mobility. Sensitivity analysis and comprehensive evaluation yield powerful insights into the robustness and adaptability of solutions. With these findings at their disposal, policymakers will be more equipped to take on unpredictability and take advantage of opportunities for sustainable urban mobility. To enhance urban transportation solutions in the dynamic metaverse, future strategies should concentrate on improving processes and exploring novel technology. Ultimately, this research emphasises how critical it is to foster interdisciplinary collaboration and ongoing innovation if we hope to influence the patterns of urban mobility in the metaverse.

He Peng, Yao Sun, Jianli Hao, Chunjiang An · 5 authors

Ground transportation, which includes the road and rail sectors, is a major source of greenhouse gas (GHG) emissions. An emissions trading system (ETS) is one of the environmental policies for controlling carbon emissions from fossil fuel combustion during transport activities. To investigate the status of existing ETS interventions on ground transportation emissions, a comprehensive literature review is conducted, including policy evaluation and comparison, scheme optimization and design, and specific transport behavior interventions. The results show that existing upstream policies are insufficient in stringency and effectiveness, while policy implementation for downstream interventions remains limited. To address these shortcomings, this study proposes a downstream ground transportation emissions trading system (GTETS), incorporating the Internet of Things and blockchain technology. As well as road and rail transportation emissions, the system includes the emissions-related activities of individuals and transportation companies, and its Web3-based technologies provide effective and efficient monitoring, reporting, and verification.

B. Balázs, Tamás Vicsek, Gergő Somorjai, Tamás Nepusz · 5 authors

Abstract Coordination of local and global aerial traffic has become a legal and technological bottleneck as the number of unmanned vehicles in the common airspace continues to grow. To meet this challenge, automation and decentralization of control is an unavoidable requirement. In this paper, we present a solution that enables self-organization of cooperating autonomous agents into an effective traffic flow state in which the common aerial coordination task—filled with conflicts—is resolved. Using realistic simulations, we show that our algorithm is safe, efficient, and scalable regarding the number of drones and their speed range, while it can also handle heterogeneous agents and even pairwise priorities between them. The algorithm works in any sparse or dense traffic scenario in two dimensions and can be made increasingly efficient by a layered flight space structure in three dimensions. To support the feasibility of our solution, we show stable traffic simulations with up to 5000 agents, and experimentally demonstrate coordinated aerial traffic of 100 autonomous drones within a 250 m wide circular area.

Berry Gerrits, Wouter van Heeswijk, Martijn Mes

Abstract Deploying self‐organizing systems is a way to cope with the logistics sector's complex, dynamic, and stochastic nature. In such systems, automated decision‐making and decentralized or distributed control structures are combined. Such control structures reduce the complexity of decision‐making, require less computational effort, and are therefore faster, reducing the risk that changes during decision‐making render the solution invalid. These benefits of self‐organizing systems are of interest to many practitioners involved in solving real‐world problems in the logistics sector. This study, therefore, identifies and classifies research related to self‐organizing logistics (SOL) with a focus on transportation. SOL is an interdisciplinary study across many domains and relates to other concepts, such as agent‐based systems, autonomous control, and decentral systems. Yet, few papers directly identify this as self‐organization. Hence, we add to the existing literature by conducting a systematic literature review that provides insight into the field of SOL. The main contribution of this paper is two‐fold: (i) based on the findings from the literature review, we identify and synthesize 15 characteristics of SOL in a typology, and (ii) we present a two‐dimensional SOL framework alongside the axes of autonomy and cooperativity to position and contrast the broad range of literature, thereby creating order in the field of SOL and revealing promising research directions.

Xi Chen, Wei Hu, Jingru Yu, Ding Wang · 7 authors

Urban growth sometimes leads to rigid infrastructure that struggles to adapt to changing demand. This paper introduces a novel approach, aiming to enable cities to evolve and respond more effectively to such dynamic demand. It identifies the limitations arising from the complexity and inflexibility of existing urban systems. A framework is presented for enhancing the city's adaptability perception through advanced sensing technologies, conducting parallel simulation via graph-based techniques, and facilitating autonomous decision-making across domains through decentralized and autonomous organization and operation. Notably, a symbiotic mechanism is employed to implement these technologies practically, thereby making urban management more agile and responsive. In the case study, we explore how this approach can optimize traffic flow by adjusting lane allocations. This case not only enhances traffic efficiency but also reduces emissions. The proposed evolutionary city offers a new perspective on sustainable urban development, highliting the importance of integrated intelligence within urban systems.

Shengyue Yao, Jingru Yu, Yi Yu, Xu Jia · 8 authors

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITS.

Panagiota Katsikouli, Pietro Ferraro, Hugo Richardson, Hanson Cheng · 9 authors

The link between transport related emissions and human health is a major issue for municipalities worldwide and one of the main challenges to address in the context of Smart Cities. Specifically, Particulate Matter (PM) emissions from exhaust and non-exhaust sources are one of the main worrying contributors to air-pollution. In this paper, we challenge the notion that a ban on internal combustion engine vehicles will result in clean and safe air in our cities, since emissions from tyres and other non-exhaust sources are expected to increase in the near future. We support this claim through simple calculations, based on publicly available data from the city of Dublin, and we present a high level solution to this problem, in the form of a control mechanism and ride-sharing scheme to limit the number of vehicles and therefore maintain the amount of transport-related PM to safe levels. Thanks to the use of Distributed Ledger Technology our proposal is entirely distributed, fair and privacy preserving, which makes it ideal for application in the Smart City domain.

Antonio Bucchiarone, Martina De Sanctis, Nelly Bencomo

The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This article proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.

Emanuel Vieira, Paulo Bartolomeu, Seyed M. Hosseini, Joaquim Ferreira

The extensive use of smartphones combined with the rise in the Internet of Things adoption has fostered the emergence of several use-cases to provide added comfort and peace of mind in our everyday life. Public transportation payment in large cities, where frequent commuters and generic users often spend a significant amount of time buying and validating tickets, can become a cumbersome process. This paper presents the design and implementation of a seamless payment system named IOTApass, which handles payments through the usage of a smartphone and a distributed ledger technology to avoid the limitations of centralized payment solutions. The IOTApass enables a user to seamlessly pay for public transports using a smartphone App without explicit (user) interface interactions, thus reducing payment complexity. Besides describing the architecture, operation, and implementation of IOTApass, the paper documents its experimental validation and confirms its feasibility.

Miloš N. Mladenović, Montasir Abbas, Claudio Roncoli, Sanaz Bozorg Chenani

Development of integrated mobility and traffic management strategies is an important aspect of the ongoing transition of urban mobility systems. Extending from existing credit schemes, this research presents a system design and evaluation of a framework based on the principle of Universal Basic Mobility. In particular, using premises of long-term cooperation and hierarchical self-organization, the system design includes user-based Mobility Credits interrelated with Priority Levels. To complement the cooperation framework, system architecture is formulated in line with the distributed ledger technology. The proposed framework is tested using web-based interaction in the form of stated-preference experiment. Results are analyzed through statistical distributions and a discrete-choice model of user decision-making within the proposed framework. This research concludes that this framework could nudge uses towards reciprocity and altruism in their travelling behavior. In addition, experiment participants have provided a range of comments related to positive features, potential for failure, and further development. Finally, the paper ends by raising several implications for wider citizen participation in the integrated mobility system design and evaluation.

Caroline Jaffe, Cristina Mata, Sepandar Kamvar

As cities become increasingly dense, they must turn to novel technologies and frameworks to address the mobility challenges that will arise. 50% of trips in the U.S. are less than 3 miles, and could be replaced by a more sustainable and space-efficient mode of transportation, such as bicycling, if effective policies and incentives were implemented.

Rashid Mehmood, Royston Meriton, Gary Graham, Patrick Hennelly · 5 authors

Purpose The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model. Design/methodology/approach A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services. Findings This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers. Research limitations/implications The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities. Practical implications The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO 2 footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013). Social implications The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system. Originality/value Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

Jan K. Brueckner

This paper shows that the inefficiency of fiscal decentralization in the presence of spillovers, a main tenet of the decentralization literature, is overturned in a particular transportation context. In a monocentric city where road (bridge) capacity is financed by budget-balancing user fees, decentralized capacity choices (made by individual zones within the city) generate the social optimum despite the presence of spillovers. This conclusion is closely tied to the famous self-financing theorem of transporation economics.

Ken Gwilliam, Zhi Liu, Brendan Finn

China has the largest urban public transport sector in the world. In principle, strategic policy is determined by the central government, and passed down through the organs of state for implementation. In recent years that strategy has included giving priority to public transport and reforming the supply arrangements to secure a more commercial and competitive sector. In practice, responsibility for implementation is completely decentralized, with municipalities having both complete responsibility for financing urban public transport and substantial freedom to interpret central government guidance at the local level. This paper considers the reforms that have already occurred under this regime, the constraints and limitations on the reform process, and the most recent initiatives being undertaken. It shows that a very wide range of systems are being experimented with simultaneously, with so far no sign that central government would intervene in detail or to provide central government finance specifically for the sector.

Andrew Kiggundu

ABSTRACT\nPrioritizing public tramjport in large cities requires huge amount of money.\nIn Kuala Lumpur for example, public transport services are relatively poor and inefficient due in part to the inability by the major operators to mobilize ample investment capital. Besides, the new funding systems such as the Public Transportation Trust Fund (PTTF) may not be able to solve the problem because they are still unclear and incoherent. Other key challenges are: lack of a pro-transit policy. rapid motorization. urban decentralization as well as dependence on fare\nrevenue and banks to fund new investments. CrucianF. due to the poor design of private rail concessions, government intervention has been inevitable.\n\nKeywords: large cities, public transit, Kuala Lumpur, funding

Phillip J. Bryson

The Czech Republic and Slovakia, like other transition countries in Central and Eastern Europe, have given significant lip service to fiscal decentralization and engaged in public administration reforms. But the subnational governments of their public finance systems still lack relative autonomy, which could be addressed partly through developing independent revenue sources for their municipalities and regions. Currently, such independent revenue sources include the proceeds of a strictly nominal property tax as well as those of a small set of local user fees and taxes designed and approved by the central governments. Together they represent only about 5 percent of total municipal budget revenues.

Edward W. Hill, Billie K. Geyer, Claudette Robey, John F. Brennan · 5 authors

This paper investigates the transportation expenditure geographic pattern in Ohio from 1980 to 1988. It focuses on the location and spatial patterns of state transportation spending and finance. It then compares these variables with transportation need and demand indicators. The aim of the report is to ascertain whether or not the state's transportation money is being spent appropriately to meet the many challengers occurring today in metropolitan areas. Some of these challenges include traffic congestion, aging infrastructure, and decentralizing economic development.

Saksith Chalermpong

Most economists agree that new investments in highways at this point in time in the United States have little impact on overall growth in output. New highways play a more important role in shifting economic activities among places, drawing jobs from other locations into the highway corridors, a phenomenon known as negative spillovers. The objective of this dissertation is two-fold, to examine the proposal to decentralize highway finance, which aims to solve the financial responsibility mismatch problem that stems from economic spillovers of highways, and to test the hypothesis of economic spillovers of highway investment at the metropolitan level. First, to better understand how spillovers influence the highway investment decision, the theoretical framework from the interjurisdictional tax competition literature is borrowed to model governments' investment behaviors. Numerical simulations show that decentralized local governments, which independently maximize output in their own jurisdiction, may engage in wasteful investments in highways with the presence of spillovers. Second, to shed more light on the spatial detail of economic spillovers, empirical tests of the spillover hypothesis are conducted at the metropolitan level, with census tracts as the unit of observation. The results of the quasi-experiment reveal census tract employment growth patterns that confirm the existence of negative spillovers caused by the opening of the Interstate 105 in 1993. The benefiting area, which grew substantially after the highway was opened, is limited to a long narrow corridor around the highway, while nearby locations outside the corridor experienced slow growth relative to the rest of the metropolitan area after controlling for various factors. Together, these results suggest that although negative spillovers are present at the metropolitan level, decentralizing highway finance may not be an effective policy to deal with the financial responsibility mismatch problem. Highway finance should remain centralized within metropolitan areas, and regional governing bodies should pay special attention to the distributional impact of highway projects.

David Levinson

This dissertation examines why and how jurisdictions choose to finance their roads. The systematic causes of revenue choice are explored qualitatively by examining the history of turnpikes. The question is approached analytically by employing game theory to model revenue choice on a long road. The road is covered by a series of jurisdictions seeking to maximize local welfare. Jurisdictions are responsible for building and maintaining the local network. Complexity arises because local network users may not be local residents, and local residents may use non-local networks. Key factors posited to explain the choice of revenue mechanism include the length of trips using the road, the size of the governing jurisdiction, the degree of excludability, and the transaction costs of toll collection. These factors dictate the size and scope of the free rider problem. It is hypothesized that smaller jurisdictions and lower collection costs favor tolling policies over taxes.The analytical model is operationalized by assuming jurisdictions have two decisions: the strategic decision to tax or toll, and the tactical decision of setting the rate of tax or toll. Models of user demand as a function of trip distance and monetary cost and of network costs as a function of traffic flow and the number of toll collections are specified. The values of the constants and coefficients of the model are developed from recent cost literature and the estimation of a model of collection costs from California Toll Bridge data.The model is applied to evaluate the dissertation's hypotheses. The application evaluates the welfare implications of a jurisdiction and its neighbors imposing general tax, cordon toll, odometer tax, or perfect toll policies. Sensitivity tests of the model under alternative behavioral assumptions, and with varying model coefficients are conducted. Finally, policy implications from the analysis are drawn. The general trends which bode well for road pricing (electronic toll collection (ETC), decentralization, advanced infrastructure, privatization, and federal rules) are established. Possible scenarios for three cases are presented: deploying ETC and building new toll roads, and converting free roads.

Kinji Mori

No abstract is available for this record.

Kiyotaka Shimizu, Eitaro Aiyoshi, Tetsuo Ueno

We are concerned with a class of organizations composed of a coordinating central system and plural semi-autonomous subsystems, such that each of them has a decision-making unit. Such a problem is regarded as that of a decentralized two-level optimization. The basic principle of planning for this organization is that the central system allocates resources so as to optimize its own objective, while the subsystems optimize their own objectives using the given resources.Within this framework of decision making, we consider a transportation problem in which N transport agents transport their own commodity. Each transport agent n, n=1, …, N, finds optimal flow patterns of the associated commodity n so that the transportation cost is minimized based on its own objective function under the arc capacity restriction imposed by the central agent. The coordinating central agent governs the transport agents through the way of allocating the arc capacity so that the optimality of whole network system is achieved. Here, the lower level problem is composed of a set of single commodity minimum cost flow problems of the transport agents, each of which can be easily solved separately by the subsystem.The decentralized optimization problem is solved in principle by a parametric approach. A feasible direction algorithm using directional derivative and application of a constraint simplex method are proposed to solve the formulated network flow problem.