Search Results (243)

Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs. These challenges are compounded by the dynamic nature of vehicular networks and the stringent requirements for real-time data processing and decision-making. Much research is on using novel technologies such as machine learning, blockchain, and cryptography to secure V2X communications. Our survey highlights the security challenges faced by V2X communications and assesses current ML and blockchain-based solutions, revealing significant gaps and opportunities for improvement. Specifically, our survey focuses on studies integrating ML, blockchain, and multi-access edge computing (MEC) for low latency, robust, and dynamic security in V2X networks. Based on our findings, we outline a conceptual framework that synergizes ML, blockchain, and MEC to address some of the identified security challenges. This integrated framework demonstrates the potential for real-time anomaly detection, decentralized data sharing, and enhanced system scalability. The survey concludes by identifying future research directions and outlining the remaining challenges for securing V2X communications in the face of evolving threats. 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

As a new generation of mobile communication networks, 6G security faces many new security challenges. Vehicle to Everything (V2X) will be an important part of 6G. In V2X, connected and automated vehicles (CAVs) need to frequently share data with other vehicles and infrastructures. Therefore, identity revocation technology in the authentication is an important way to secure CAVs and other 6G scenario applications. This paper proposes an efficient credential revocation scheme with a four-layer architecture. First, a rapid pre-filtration layer is constructed based on the cuckoo filter, responsible for the initial screening of credentials. Secondly, a directed routing layer and the precision judgement layer are designed based on the consistency hash and the dynamic RSA accumulator. By proposing the dynamic expansion of the RSA accumulator and load-balancing algorithm, a smaller and more stable revocation delay can be achieved when many users and terminal devices access 6G. Finally, a trusted storage layer is built based on the blockchain, and the key revocation parameters are uploaded to the blockchain to achieve a tamper-proof revocation mechanism and trusted data traceability. Based on this architecture, this paper also proposes a detailed identity credential revocation and verification process. Compared to existing solutions, this paper’s solution has a combined average improvement of 59.14% in the performance of the latency of the cancellation of the inspection, and the system has excellent load balancing, with a standard deviation of only 11.62, and the maximum deviation is controlled within the range of ±4%. Full article

The integration of autonomous vehicles (AVs) into urban transportation systems has significant potential to enhance traffic efficiency and reduce environmental impacts. This study evaluates the impact of different AV penetration scenarios (0%, 10%, 30%, 50%) on traffic performance and carbon emissions along Prince Mohammed bin Salman bin Abdulaziz Road in Riyadh, Saudi Arabia. Using microscopic simulation (SUMO) based on real-world datasets, we assess key performance indicators such as travel time, stop frequency, speed, and CO₂ emissions. Results indicate notable improvements with increasing AV deployment, including up to 25.5% reduced travel time and 14.6% lower emissions at 50% AV penetration. Coordinated AV behavior was approximated using adjusted simulation parameters and Python-based APIs, effectively modeling vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-network (V2N) communications. These findings highlight the benefits of harmonized AV–human vehicle interactions, providing a scalable and data-driven framework applicable to smart urban mobility planning. 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

Intelligent reflecting surface (IRS) has emerged as a promising solution to establish propagation paths in non-line-of-sight (NLoS) scenarios, effectively mitigating blockage challenges in direct vehicle-to-infrastructure (V2I) links. This study investigates a time-varying multi-IRS-assisted multiple-input multiple-output (MIMO) communication system, aiming to maximize the system sum rate through the joint optimization of base station (BS) precoding and IRS phase configurations. The formulated problem exhibits inherent non-convexity and time-varying characteristics, posing significant optimization challenges. To address these, we propose a low-complexity dimension-wise sine maximization (DSM) algorithm, grounded in the sum path gain maximization (SPGM) criterion, to efficiently optimize the IRS phase shift matrix. Concurrently, the water-filling (WF) algorithm is employed for BS precoding design. Simulation results demonstrate that compared with traditional methods, the proposed DSM algorithm achieves a 14.9% increase in sum rate, while exhibiting lower complexity and faster convergence. Furthermore, the proposed multi-IRS design yields an 8.7% performance gain over the single-IRS design. Full article

Digital Twins (DTs) are becoming essential tools for real-time decision-making in transportation systems. This paper presents a macroscopic traffic digital twin developed for a 50 km segment of the C-32 interurban highway in Spain. The digital twin replicates highway conditions using real-time data from roadside sensors and connected vehicles via Vehicle-to-Everything (V2X) communications. It supports intelligent decision-making for traffic management, particularly during incident situations, by recommending macroscopic strategies such as variable speed limits and re-routing. Unlike many existing DTs focused on microscopic modeling or urban contexts, our approach emphasizes a macroscopic scale suitable for interurban highways, enabling faster computation and system-wide insights. The decision-making module evaluates candidate strategies using real-time simulations and selects the most effective option based on key performance indicators (KPIs), including congestion, travel time, and emissions. The system has been validated under realistic traffic scenarios using historical data, considering both congestion and pollution use cases. Strategies are communicated back to the physical infrastructure via V2I messages (IVIM) and a mobile application using the cellular communication network, enabling a closed-loop architecture. This paper contributes a scalable, real-time, and field-integrated macroscopic DT framework for highway traffic management. Full article

Visible light communication (VLC) is considered to be one of the key technologies for advancing the next-generation intelligent transportation systems (ITSs). However, in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) VLC, the line-of-sight (LOS) link for communication is often obstructed by vehicle mobility. To address this issue and enhance system performance, a novel V2I–VLC system is proposed and analyzed in this study. The system targets mountain road traffic scenarios employing optical reflecting intelligent surfaces (RISs). To emphasize the practicality of the study, the effects of atmospheric turbulence (AT) and weather conditions are also considered in the channel modeling. Further, the closed-form expressions for average path loss, channel capacity, and outage probability are derived. Furthermore, a novel closed-form expression is also derived for the properties of RIS, which can be used to calculate the required number of RIS elements to achieve a target energy efficiency. In the performance analysis, the accuracy of the derived theoretical expression is validated by numerical simulation, and the effectiveness of the RIS-aided V2I–VLC system is evaluated. Moreover, with a reasonable number of required RIS elements, the system performance in terms of path loss is improved by more than 23.5% on average over the existing studies. Full article

Ensuring reliable communication in remote or disaster-affected areas is a technical challenge due to unplanned deployment and mobilization, meaning placement difficulties and high operation costs of conventional telecommunications infrastructures. To address this problem, unmanned aerial vehicles (UAVs) have emerged as an excellent alternative to provide quick connectivity in remote or disaster-affected regions at a reasonable cost. However, the limited battery autonomy of UAVs restricts their flight service time. This paper proposes a communication system based on a tethered UAV (T-UAV) capable of continuous operation through a wired power network connected to a ground station. The communications system is based on low-cost devices, such as Raspberry Pi platforms, and offers wireless IP telephony services, providing high-quality and reliable communication. Experimental tests assessed power consumption, UAV stability, and data transmission performance. Our results prove that the T-UAV, based on a quadcopter drone, operates stably at 16 V and 20 A, ensuring consistent VoIP communications at a height of 10 m with low latency. These experimental findings underscore the potential of T-UAVs as cost-effective alternatives for extending or providing communication networks in remote regions, emergency scenarios, or underserved areas. Full article

The introduction of Bus Rapid Transit (BRT) systems has the potential to alleviate urban traffic congestion. However, in certain cities in China, the increasing prevalence of privately owned vehicles, combined with the underutilization of bus lanes due to infrequent bus departures, has contributed to heightened congestion in general lanes. The advent of Internet of Things (IoT) technology offers a promising opportunity to develop intelligent public transportation systems, facilitating efficient management through seamless information transmission to end devices. This paper presents an IoT-based shared bus lane (IoT-SBL) that integrates intersection information, real-time traffic queuing conditions, and bus location data to encourage passenger vehicles to utilize the bus lane. This encouragement can be communicated through traditional signaling methods or future Infrastructure-to-Vehicle (I2V) and Vehicle-to-Vehicle (V2V) communication technologies. To evaluate the effectiveness of the IoT-SBL strategy, we proposed a stochastic model that incorporates queuing effects and derived a series of performance metrics through model analysis. The experimental findings indicated that the IoT-SBL strategy significantly reduces vehicle queuing, decreases vehicle delays, enhances intersection throughput efficiency, and lowers fuel consumption compared to the traditional bus lane strategy. 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

As an important part of the Internet of Things, the Internet of Vehicles (IoV) has achieved efficient interconnection and collaboration between vehicles and road infrastructure, and between vehicles through advanced information and communication technologies. However, the high-speed movement of vehicles has generated a large number of cross-domain behaviors, which has greatly increased the number of authentications. Existing authentication protocols face challenges such as high cost, high computational overhead, and easy eavesdropping, interception, or tampering. To this end, this paper proposes an ECC-based IoV secure and efficient handover authentication protocol. The protocol adopts a “non-full key escrow” mechanism. The private key of the vehicle is jointly generated by the Trusted Authority (TA) and the vehicle. The TA only holds part of the private key. Even if the TA is malicious, the security of the vehicle’s private key can be ensured. At the same time, the proposed protocol uses the time tree technology in trusted computing to share part of the vehicle’s private data, which not only ensures the security of authentication, but also improves the efficiency of authentication, and solves the high-latency problem caused by the use of blockchain in previous protocols. When the vehicle moves across domains, there is no need to re-register and authenticate, which reduces the authentication overhead. Compared with existing protocols, this protocol is lightweight in both computational and communication overheads, effectively solving the problem of excessive cost. Full article

With the explosion of vehicle-to-infrastructure (V2I) communications in the internet of vehicles (IoV), it is still very important to ensure secure authentication and efficient key agreement because of the vulnerabilities in the existing protocols such as physical capture attacks, privacy leakage, and low computational efficiency. This paper proposes a physical unclonable function (PUF)-based multi-factor authentication and key agreement protocol tailored for V2I environments, named as PMAKA-IoV. The protocol integrates hardware-based PUFs with biometric features, utilizing fuzzy extractors to mitigate biometric template risks, while employing dynamic pseudonyms and lightweight cryptographic operations to enhance anonymity and reduce overhead. Security analysis demonstrates its resilience against physical capture attacks, replay attacks, man-in-the-middle attacks, and desynchronization attacks, and it is verified by formal verification using the strand space model and the automated Scyther tool. Performance analysis demonstrates that, compared to other related schemes, the PMAKA-IoV protocol maintains lower communication and storage overhead. Full article

The progress in automotive technology, communication protocols, and embedded systems has propelled the development of the Internet of Vehicles (IoV). In this system, each vehicle acts as a sophisticated sensing platform that collects environmental and vehicular data. These data assist drivers and infrastructure engineers in improving navigation safety, pollution control, and traffic management. Digital artefacts stored within vehicles can serve as critical evidence in road crime investigations. Given the interconnected and autonomous nature of intelligent vehicles, the effective identification of road crimes and the secure collection and preservation of evidence from these vehicles are essential for the successful implementation of the IoV ecosystem. Traditional digital forensics has primarily focused on in-vehicle investigations. This paper addresses the challenges of extending artefact identification to an IoV framework and introduces the Collaborative Forensic Platform for Electronic Artefacts (CFPEA). The CFPEA framework implements a collaborative forensic-by-design mechanism that is designed to securely collect, store, and share artefacts from the IoV environment. It enables individuals and groups to manage artefacts collected by their intelligent vehicles and store them in a non-proprietary format. This approach allows crime investigators and law enforcement agencies to gain access to real-time and highly relevant road crime artefacts that have been previously unknown to them or out of their reach, while enabling vehicle owners to monetise the use of their sensed artefacts. The CFPEA framework assists in identifying pertinent roadside units and evaluating their datasets, enabling the autonomous extraction of evidence for ongoing investigations. Leveraging CFPEA for artefact collection in road crime cases offers significant benefits for solving crimes and conducting thorough investigations. Full article

Sustainable mobility in university environments presents both a challenge and an opportunity to reduce environmental impact and promote energy efficiency. This study assesses the feasibility of implementing electric buses in the internal transportation system of the Federal University of Paraíba (UFPB), considering environmental, economic, and operational aspects. The analysis demonstrates that transitioning to this model can lead to a significant reduction in greenhouse gas (GHG) emissions, noise pollution mitigation, and optimization of operational costs throughout the vehicle’s life cycle. The study examines technical, structural, and financial factors, emphasizing the necessary infrastructure, academic community acceptance, and the economic viability of the project, as well as the strategic advantage of integrating the electric fleet with photovoltaic energy generation. The key highlights of this research include: (i) Sustainability and energy efficiency, emphasizing a reduction of up to 52.52% in CO₂ emissions when vehicles are powered by photovoltaic energy in an LCA context, alongside improvements in air quality and noise pollution mitigation. (ii) Economic feasibility analysis, comparing operational and maintenance costs between electric and conventional diesel buses, evaluating the financial viability and potential return on investment. (iii) Infrastructure and implementation challenges, addressing the need for charging stations, adaptation of UFPB’s infrastructure, and financing models, including government subsidies and strategic partnerships. (iv) Impact on the academic community, analyzing student and staff perceptions and acceptance of fleet electrification and the promotion of sustainable practices. (v) Future projections and replicability, exploring trends in the sustainable transportation sector, as well as the potential expansion of the electric fleet and its integration with energy storage systems. The results indicate that adopting electric buses at UFPB can position the institution as a benchmark in sustainable mobility, serving as a replicable model for other universities and contributing to carbon emission reduction and modernization of university transportation. Full article