Blockchain Papers

Mihhail Kirejev, Wolfgang Gerstlberger, Tarvo Niine

No abstract is available for this record.

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.

Ramakrishnan Raman, Sujata Arya

The demand for advanced traffic management systems in smart cities has grown in recent years in response to rising urban populations and the increasing importance of environmental preservation. With the use of the Internet of Things (IoT), it investigates how Distributed Ledger Technology (DLT) may be implemented in decentralized virtual traffic signal systems. To overcome the drawbacks of conventional traffic light regulation, the suggested approach decentralizes the decision-making process over a set of interconnected devices. Integration of DLT, like blockchain, improves the system's openness, security, and robustness. Connected sensors and actuators in the IoT make it possible to gather and share real-time data, and techniques for traffic management that is both responsive and aware of its surroundings. To improve traffic flow, the virtual traffic light system's decentralized design helps save resources and lessens the system's overall carbon footprint. This article describes the system's technological architecture, explores its potential advantages, and explains how it may revolutionize urban traffic management for creating smart cities that are both sustainable and resilient.

Zhaokun Li, Luteng Wang, G F Wang, Xu Xin · 6 authors

No abstract is available for this record.

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.

Jiali Yang, Kehua Yang, Zhu Xiao, Hongbo Jiang · 6 authors

With deepening urbanization and Internet of Vehicles (IoV) applications, the number of private cars has been increasing in recent years. However, because the surging number of private cars is not compatible with limited road resources, private car users have had unsatisfactory commute experiences during their daily travel. In this work, we focus on improving private car users’ commute experience based on an analysis of IoV trajectory data in a privacy-preserving way. Our idea is based on the following observations: 1) the commute experience of private car users is closely related to the departure time and the travel cost and 2) most travel costs are spent on urban hot zones. Motivated by these findings, we propose a novel blockchain-enabled model named Deep Improving Commute Experience (DeepICE) to improve private car users’ commute experience by predicting when to depart and when to arrive. In this model, a blockchain with a consensus mechanism is developed to address private car user privacy concerns. In addition, we propose a multitask learning-enabled graph convolution network (GCN) method to capture the highly complex features and relations between two tasks, i.e., the departure time and travel cost, and then develop the model to predict these two tasks. The experimental results demonstrate the superior performance of our proposed model compared to existing approaches. Our model can be applied to efficiently enhance private car users’ commute experience.

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.

Tian Luo, Daofang Chang, Zhenyu Xu, Xiaoyuan Hu

No abstract is available for this record.

Dong-Hoon Son

No abstract is available for this record.

Mustapha Oudani

No abstract is available for this record.

Chen Zhao, Yisheng Lv, Junchen Jin, Yonglin Tian · 6 authors

Parallel transportation management and control was proposed three decades ago as a new paradigm for conducting complex transportation operations and has led to today’s DeCAST in TransVerse platform designed and constructed according to the principle of decentralized/distributed autonomous operations and organizations. This article presents an overview of its architectures, processes, operating procedures, and major applications. The developments and applications have demonstrated clearly that parallel transportation systems are effective for networked traffic control and distributed logistical operations. The existing challenges and emerging opportunities are also addressed. A transportation foundation model based on parallel learning and federated intelligence is proposed as a potential path to the next-generation parallel intelligent transportation systems.

Zhixiang Zhou, Yuanfei Ma, Yinghao Pan, Yangguang Zhu

No abstract is available for this record.

Geeta Rani, Gogula Narasimha Murthy, Madhurapantula Abhiram, Harini Mohan · 6 authors

The recent Airlines management is facing lots of challenges and the pandemic has made it more critical. The airlines' industry needs to come up with a strong solution to uplift the airlines' sector and sophisticate the customers. In this paper, the main objective of the Airlines reservation system is to implement software using java that accompanies blockchain technology considering the airline sector challenges. It helps users to reserve tickets for air service and track the updated status periodically. Blockchain technology keeps the data secured and centralized providing efficient usage via mobile apps or online. The system provides an efficient user interface for both customers and stakeholders and analyzes the behavior of the customer and provides efficient results. This article also explains the demand price prediction and related challenges to be solved efficiently. All the above factors are considered and an efficient solution of application system using Java.

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.

Vikas Hassija, Vatsal Gupta, Sahil Garg, Vinay Chamola

The exponential surge in the number of vehicles on the road has aggravated the traffic congestion problem across the globe. Several attempts have been made over the years to predict the traffic scenario accurately and consequently avoiding further congestion. Crowdsourcing has come forward as one of the most adopted methods for predicting traffic intensity using live data. However, the privacy concerns and the lack of motivation for the live users to help in the traffic prediction process have rendered existing crowdsourcing models inefficient. Towards this end, we present an advanced blockchain-based secure crowdsourcing model. Not only does our model ensure privacy preservation of the users, but by incorporating a revenue model, it also provides them with an incentive to participate in the traffic prediction process willingly. For accurate and efficient traffic jam probability estimation, our work proposes a neural network-based smart contract to be deployed onto the blockchain network. The results reveal that the proposed model is highly efficient in terms of attaining high participation and consequently obtaining highly accurate predictions.

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.

Ganesan Muniandi

Railway traffic conflicts are common in the day‐to‐day operation of trains due to the limited track capacity, the varying priority of trains, localised weather conditions, maintenance operations etc. The conventional conflict resolution strategy focuses on delaying the trains by considering the braking distance of a preceding train, cancellation or intermediate stopping of the trains etc. This strategy can solve the problem of railway operators than the passenger's problem of missed connecting trains, missed business opportunities or personal appointments etc. To ensure both operator and passenger satisfaction, this paper proposes a novel blockchain‐enabled virtual coupling of automatic train operation fitted mainline trains for railway traffic conflicts. The immutable blockchain databases of the trains and track infrastructures help to forecast the traffic conflicts in real time. Seven variants of virtual coupling strategies are described in this study. Based on the chosen strategy, the reference model of the automatic train operation of mainline trains is virtually coupled or synchronised. Finally, the simulation results and theoretical analyses using several case studies are carried out to confirm the sufficiency of the proposed system and method. The major advantage of the proposed study is that it can be an overlay to the existing European Railway Traffic Management System Level‐2.