Search Results (205)

Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater manipulation, and the alternative of using professional divers is ruled out due to the risk involved. This work presents and experimentally validates an autonomous, dual-I-AUV (Intervention–Autonomous Underwater Vehicle) system capable of assembling rigid pipeline segments through coordinated actions in a confined underwater workspace. The first I-AUV is a Girona 500 (4-DoF vehicle motion, pitch and roll stable) fitted with multiple payload cameras and a 6-DoF Reach Bravo 7 arm, giving the vehicle 10 total DoF. The second I-AUV is a BlueROV2 Heavy equipped with a Reach Alpha 5 arm, likewise yielding 10 DoF. The workflow comprises (i) detection and grasping of a coupler pipe section, (ii) synchronized teleoperation to an assembly start pose, and (iii) assembly using a kinematic controller that exploits the Girona 500’s full 10 DoF, while the BlueROV2 holds position and orientation to stabilize the workspace. Validation took place in a 12 m × 8 m × 5 m water tank. Results show that the paired I-AUVs can autonomously perform precision pipeline assembly in real water conditions, representing a significant step toward fully automated subsea construction and maintenance. Full article

The swift advancements in autonomous vehicle systems have facilitated their implementation across various industries, including agriculture. However, studies primarily focus on passenger vehicles, with fewer examining autonomous trucks. Therefore, this study reviews autonomous truck systems implementation in North Dakota’s agricultural industry to develop comprehensive technology readiness frameworks and strategic deployment approaches. The review integrates systematic literature review and event history analysis of 52 studies, categorized using Social–Ecological–Technological Systems framework across six dimensions: technological, economic, social change, legal, environmental, and implementation challenges. The Technology Readiness Level (TRL) analysis reveals 39.5% of technologies achieving commercial readiness (TRL 8–9), including GPS/RTK positioning and V2V communication demonstrated through Minn-Dak Farmers Cooperative deployments, while gaps exist in TRL 4–6 technologies, particularly cold-weather operations. Nonetheless, challenges remain, including legislative fragmentation, inadequate rural infrastructure, and barriers to public acceptance. The study provides evidence-based recommendations that support a strategic three-phase deployment approach for the adoption of autonomous trucks in agriculture. Full article

The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into logistics centers. This study proposes a comprehensive multi-criteria evaluation framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the suitability of ten candidate sites. The evaluation criteria span four dimensions, facility, geographical, environmental, and social factors, derived from the literature and expert consultations. AHP results indicate that geographical factors, especially proximity to urban centers and major logistics facilities, hold the highest weight. Based on the integrated analysis using TOPSIS, the most suitable locations identified are Sinnae, Godeok, and Cheonwang. The findings suggest the strategic importance of aligning infrastructure development with spatial accessibility and stakeholder cooperation. Policy implications include the need for targeted investment, public–private collaboration, and sustainable logistics planning. Future research is encouraged to incorporate dynamic data and consider social equity and environmental impact for long-term urban logistics planning. Full article

As global climate change intensifies and the transition to clean energy accelerates, lithium-ion batteries—critical components of electric vehicles—are becoming increasingly vital in international trade networks. This study investigates the structural evolution and determinants of the electric vehicle lithium-ion battery trade network among European Union (EU) member states from 2012 to 2023, employing social network analysis and the multiple regression quadratic assignment procedure method. The findings demonstrate the transformation of the network from a centralized and loosely connected structure, with Germany as the dominant hub, to a more interconnected and decentralized system in which Poland and Hungary emerge as the leading players. Key network metrics, such as the density, clustering coefficients, and average path lengths, reveal increased regional trade connectivity and enhanced supply chain efficiency. The analysis identifies geographic and economic proximity, logistics performance, labor cost differentials, energy resource availability, and venture capital investment as significant drivers of trade flows, highlighting the interaction among spatial, economic, and infrastructural factors in shaping the network. Based on these findings, this study underscores the need for targeted policy measures to support Central and Eastern European countries, including investment in logistics infrastructure, technological innovation, and regional cooperation initiatives, to strengthen their integration into the supply chain and bolster their export capacity. Furthermore, fostering balanced inter-regional collaborations is essential in building a resilient trade network. Continued investment in transportation infrastructure and innovation is recommended to sustain the EU’s competitive advantage in the global electric vehicle lithium-ion battery supply chain. Full article

This paper provides a comprehensive review of the development, deployment and challenges of Intelligent Transport Systems (ITSs) in Europe. Driven by the EU Directive 2010/40/EU, the deployment of ITSs has become essential for improving the safety, efficiency and sustainability of transport. The study examines how ITS technologies, such as automation, real-time traffic data analytics and vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, have been integrated to improve urban mobility and road safety. In addition, it reviews significant European initiatives and case studies from several cities, which show visible improvements in reducing congestion, reducing CO₂ emissions and increasing the use of public transport. The paper highlights, despite progress, major obstacles to widespread adoption, such as technical interoperability, inadequate regulatory frameworks and insufficient data sharing between stakeholders. These issues prevent ITS applications from scaling up and functioning well in EU Member States. To overcome these problems, the study highlights the need for common standards and cooperation frameworks. The research analyses the laws, technological developments and socio-economic effects of ITSs. By promoting sustainable and inclusive mobility, ITSs can contribute to the European Green Deal and climate goals. Finally, the paper presents ITSs as a revolutionary solution for future European transport systems and offers suggestions to improve their interoperability, data governance and policy support. Full article

This study critically reflects on Myanmar’s readiness and potential to transition from internal combustion engine (ICE) vehicles to electric vehicles (EVs) amidst escalating climate pressures, energy insecurity, and regional technological shifts. It aims to advocate a systemic and inclusive EV strategy rooted in environmental, economic, and governance imperatives. Drawing on an extensive review of scholarly literature, policy documents, and regional best practices, this study synthesizes evidence to frame a normative argument for accelerating the adoption of EVs in Myanmar. It combines the environmental, infrastructural, and political–economic perspectives to support its position. Myanmar’s EV transition is not merely a technological leap, but a structural transformation intertwined with energy equity, public health, and geopolitical positioning. While significant barriers, such as grid unreliability, policy inconsistency, and socioeconomic disparities, persist, coordinated national efforts and regional cooperation can unlock transformative opportunities. Policy clarity, grid modernization, public engagement, and international partnerships are essential enablers. This study offers a timely and region-specific perspective on the EV debate, highlighting Myanmar’s unique vulnerabilities and latent advantages. It presents a value-based call for inclusive, future-oriented policymaking that aligns Myanmar’s mobility system with its sustainability and development goals. Full article

Recent advancements in cooperative 3D object detection have demonstrated significant potential for enhancing autonomous driving by integrating roadside infrastructure data. However, deploying comprehensive LiDAR-based cooperative perception systems remains prohibitively expensive and requires precisely annotated 3D data to function robustly. This paper proposes an improved multi-modal method integrating LiDAR-based shape references into a previously mono-camera-based semantic vertex reconstruction framework to enable robust and cost-effective monocular and cooperative pose estimation after the reconstruction. A novel camera–LiDAR loss function that combines re-projection loss from a multi-view camera system alongside LiDAR shape constraints is proposed. Experimental evaluations conducted on the Argoverse dataset and real-world experiments demonstrate significantly improved shape reconstruction robustness and accuracy, thereby improving pose estimation performance. The effectiveness of the algorithm is proven through a real-world smart valet parking application, which is evaluated in our university parking area with real vehicles. Our approach allows accurate 6DOF pose estimation using an inexpensive IP camera without requiring context-specific training, thereby advancing the state of the art in monocular and cooperative image-based vehicle localization. Full article

As urban populations expand and congestion intensifies, traditional ground transportation struggles to satisfy escalating mobility demands. Unmanned Electric Vertical Take-Off and Landing (eVTOL) aircraft, as a key enabler of Urban Air Mobility (UAM), leverage low-altitude airspace to alleviate ground traffic while offering environmentally sustainable solutions. However, supporting high bandwidth, real-time video applications, such as Virtual Reality (VR), Augmented Reality (AR), and 360° streaming, remains a major challenge, particularly within bandwidth-constrained metropolitan regions. This study proposes a novel Unmanned Aerial Vehicle (UAV)-enabled video streaming architecture that integrates 6G wireless technologies with intelligent routing strategies across cooperative airborne nodes, including unmanned eVTOLs and High-Altitude Platform Systems (HAPS). By relaying video data from low-congestion ground base stations to high-demand urban zones via autonomous aerial relays, the proposed system enhances spectrum utilization and improves streaming stability. Simulation results validate the framework’s capability to support immersive media applications in next-generation autonomous air mobility systems, aligning with the vision of scalable, resilient 3D transportation infrastructure. Full article

To address the limitations of traditional single-motor bionic ornithopters in terms of environmental adaptability and lift capacity, this study proposes a dual-motor independently driven system utilizing a cross-shaft single-gear crank mechanism to achieve adjustable flap speed and wing frequency, thereby enabling asymmetric flapping for enhanced environmental adaptability. The design integrates a two-stage reduction gear group to optimize torque transmission and an S1223 high-lift airfoil to improve aerodynamic efficiency. Multiphysics simulations combining computational fluid dynamics (CFD) and finite element analysis (FEA) demonstrate that, under flapping frequencies of 1–3.45 Hz and wind speeds of 1.2–3 m/s, the optimized model achieves 50% and 60% improvements in lift and thrust coefficients, respectively, compared to the baseline. Concurrently, peak stress in critical components (e.g., cam disks and wing rods) is reduced by 37% to 41 MPa, with significantly improved stress uniformity. These results validate the dual-motor system’s capability to dynamically adapt to turbulent airflow through the precise control of wing kinematics, offering innovative solutions for applications such as aerial inspection and precision agriculture. Full article

In a multi-beam communication scenario where Infrastructure-to-Vehicle (I2V) and Vehicle-to-Vehicle (V2V) communications coexist, the limited spectrum of resources force V2V users to reuse the orthogonal frequency bands allocated to I2V, inevitably introducing cross-layer interference between I2V and V2V. Furthermore, the adoption of a multi-beam communication architecture exacerbates beam interference, significantly degrading the overall network’s communication and sensing performance. To address these challenges, this paper proposes an integrated sensing and communication (ISAC) beam allocation algorithm, termed IMSBA, which jointly optimizes beam direction, transmission power, and spectrum resource allocation to effectively mitigate the interference between I2V and V2V while maximizing the overall network performance. Specifically, IMSBA employs a joint optimization framework combining Multi-Agent Proximal Policy Optimization (MAPPO) with a Stackelberg game. Within this framework, MAPPO leverages vehicle perception data to dynamically optimize V2V beam steering and frequency selection, while the Stackelberg game reduces computational complexity through hierarchical decision-making and optimizes the joint power allocation among V2V users. Additionally, the proposed scheme incorporates a V2V cooperative sensing domain-sharing mechanism to enhance system robustness under adverse conditions. The experimental results demonstrated that, compared with existing baseline schemes, IMSBA achieved a 92.5% improvement in V2V energy efficiency while significantly enhancing both communication and sensing performance. This study provides an efficient and practical solution for spectrum-constrained scenarios in millimeter-wave Internet-of-Things (IoT), offering substantial theoretical insights and practical value for the efficient operation of intelligent transportation system (ITSs). Full article

With increasing vehicle density and growing demands on transport infrastructure, there is a need for resilient, low-cost communication systems capable of supporting safety-critical applications, especially in situations where primary channels like Wi-Fi or LTE are unavailable. This paper proposes a novel, real-time vehicular network protocol that functions as an emergency fallback communication layer using long-range LoRa modulation and off-the-shelf hardware. The core contribution is a development of Mobile Cell Broadcast Protocol that is implemented using Long-Range modulation and time-division multiple access (TDMA)-based cell broadcast protocol (LoRA TDMA) capable of supporting up to six dynamic clients to connect and exchange lightweight cooperative awareness messages. The system achieves a sub-100 ms node notification latency, meeting key low-latency requirements for safety use cases. Unlike conventional ITS stacks, the focus here is not on full-featured data exchange but on maintaining essential communication under constrained conditions. Protocol has been tested in laboratory to check its ability to ensure real-time data exchange between dynamic network nodes having 14 bytes of payload per data packet and 100 ms network member notification latency. While focused on vehicular safety, the solution is also applicable to autonomous agents (robots, drones) operating in infrastructure-limited environments. Full article

The intelligent connected vehicle (ICV) industry encounters substantial challenges related to technology, policies, and funding. Its development relies not only on the close collaboration and technological innovation between carmakers and technology companies but also on the support of government’s incentive policies. Therefore, this paper establishes a tripartite evolutionary game model that involves governments, carmakers, and technology companies to investigate the stability equilibrium strategy of multi-party participation in promoting the development of the ICV industry. In addition, by analyzing relevant regulations and company annual reports, this paper conducts a simulation analysis to examine how government incentive policies and benefit distribution mechanisms impact the evolutionary trajectory. Several insightful and practical conclusions are drawn. First, in the early stages of industrial development, the government’s infrastructure investment could promote the cross-border innovation cooperation between carmakers and technology companies, thereby accelerating the advancement of ICVs; however, the long-term impact of the sustained investment remains limited. Second, the incremental government subsidies for carmakers and technology companies within limits could increase the probability of them choosing to cooperate and innovate with each other. Still, the excessive subsidies could result in unstable industry growth. Finally, the increase in the benefit distribution ratio for carmakers with professional technology in automotive technology and vehicle design has a positive effect on the development of the ICV industry. This paper expands the research scope of ICVs and provides theoretical insights for promoting the sustainable development of the ICV industry from policy and market viewpoints. Full article

Today’s urban environments are complex, highly congested traffic scenarios that suffer from multiple unsolved problems such as traffic jams and congestion. These problems pose a significant increase in the risks and probability of traffic accidents in modern cities, which have experienced an enormous growth in the number of vehicles. This work introduces a centralized arbitration framework designed for Cooperative Connected Automated Vehicles (CCAVs) to make real-time decisions and resolve conflicts among various driving strategies or behaviors to facilitate resource reservation based on their collaborative actions. Cooperation and arbitration are two of the most important areas of research that seek to provide tools and mechanisms for the optimization and control of traffic flow at critical locations such as intersections and traffic circles. The approach presented, fully implemented on ROS and capable of constructing a software-defined traffic control environment, is able to supervise in a distributed manner how any CCAV operates with the infrastructure, potentially reducing the number of vehicles waiting and harmonizing the traffic flow. The methodology proposed surpasses traditional driver-in-the-loop cooperation by delivering a higher level of automation for collaborative traffic behavior. This approach demonstrably reduces average waiting time by 13% and increases the total utilization of the traffic emplacement by 70% compared to the classic simulated traffic light model. The solution presented was tested on the Carla simulator, with a complete ROS-based vehicle automation solution that provides promising results for CCAV coordination in complex traffic scenarios through a general framework of behavior-based collaboration. Full article

Vehicle-to-Vehicle (V2V) communications technology offers enhanced road safety, traffic efficiency, and connectivity. In V2V, vehicles cooperate by broadcasting safety messages to quickly detect and avoid dangerous situations on time or to avoid and reduce congestion. However, vehicles might misbehave, creating false information and sharing it with neighboring vehicles, such as, for example, failing to report an observed accident or falsely reporting one when none exists. If other vehicles detect such misbehavior, they can report it. However, false accusations also constitute misbehavior. In disconnected areas with limited infrastructure, the potential for misbehavior increases due to the scarcity of Roadside Units (RSUs) necessary for verifying the truthfulness of communications. In such a situation, identifying malicious behavior using a standard misbehaving management system is ineffective in areas with limited connectivity. This paper presents a novel mechanism, Distributed Reputation for Accurate Misbehavior Reporting (DRAMBR), offering a fully integrated reputation solution that utilizes reputation to enhance the accuracy of the reporting system by identifying misbehavior in rural networks. The system operates in two phases: offline, using the Local Misbehavior Detection Mechanism (LMDM), where vehicles detect misbehavior and store reports locally, and online, where these reports are sent to a central reputation server. DRAMBR aggregates the reports and integrates DBSCAN for clustering spatial and temporal misbehavior reports, Isolation Forest for anomaly detection, and Gaussian Mixture Models for probabilistic classification of reports. Additionally, Random Forest and XGBoost models are combined to improve decision accuracy. DRAMBR distinguishes between honest mistakes, intentional deception, and malicious reporting. Using an existing mechanism, the updated reputation is available even in an offline environment. Through simulations, we evaluate our proposed reputation system’s performance, demonstrating its effectiveness in achieving a reporting accuracy of approximately 98%. The findings highlight the potential of reputation-based strategies to minimize misbehavior and improve the reliability and security of V2V communications, particularly in rural areas with limited infrastructure, ultimately contributing to safer and more reliable transportation systems. Full article

As the global ecological environment faces serious challenges and extreme climate change threatens the survival of humankind, the promotion of green development has become the focus for all countries in the world. As one of the world’s major greenhouse gas emitters, China has put forward the “twin goals” of achieving carbon peaking and carbon neutrality and is committed to promoting the green and low-carbon transformation of its cities. As the core of economic and social development, cities are the main source of carbon emissions. In response to the dual challenges of carbon emission control and traffic growth, it is particularly important to promote the development of green transportation. With the acceleration of urbanization, urban traffic pollution is becoming more and more serious. As a zero-emission transportation mode, electric vehicles have become a key way to achieve the carbon peak and carbon neutrality targets. In order to deeply analyze the research status of electric vehicles in the field of the green and low-carbon transformation of urban transportation in China and to explore the research hot spots, evolution trends, and their roles and strategies in the construction of green transportation networks, this paper uses the CiteSpace, VOSviewer, and Tableau analysis tools to review and analyze the 2460 articles and reviews in the Web of Science Core Collection (WOS) and 2650 articles and reviews in the China National Knowledge Infrastructure (CNKI), including the “publication volume and publication trend”, “subject citation path”, “countries cooperation and geographical distribution”, “author cooperation and institution cooperation”, “keyword co-occurrence and keywords clusters”, and the “evolution trend of research hot spots in timeline”. The results show that: (1) Since 2010, the research focus on electric vehicles has gradually increased, and especially in the past three years, the number of such publications has increased significantly. (2) China holds the lead in research output regarding electric vehicles and related fields, but its international cooperation needs to be strengthened. (3) In recent years, the research has focused on “energy transformation”, “energy-saving technology”, “carbon emissions”, “battery recycling”, and other relevant topics. The promotion and development of electric vehicles will continue to usher in new opportunities concerning technological innovation, policy support, and market expansion. Finally, based on the research hot spots and evolution trends of electric vehicles in the field of urban green transportation and low-carbon transportation in China, this paper discusses the key paths and strategies for electric vehicles to promote the transformation of urban transportation in China to green and low-carbon types and looks forward to future research directions. The research in this paper can provide theoretical support and practical guidance for China to promote electric vehicles, build low-carbon cities, and realize green transportation. It is expected to act as a useful reference for relevant policy formulation and academic research. Full article