Hasil untuk "Transportation and communication"

Panos Papadimitratos, A. D. L. Fortelle, Knut Evenssen et al.

P. Hancock, I. Nourbakhsh, J. Stewart

Automated vehicles (AVs) already navigate US highways and those of many other nations around the world. Current questions about AVs do not now revolve around whether such technologies should or should not be implemented; they are already with us. Rather, such questions are more and more focused on how such technologies will impact evolving transportation systems, our social world, and the individuals who live within it and whether such systems ought to be fully automated or remain under some form of direct human control. More importantly, how will mobility itself change as these independent operational vehicles first share and then dominate our roadways? How will the public be kept apprised of their evolving capacities, and what will be the impact of science and the communication of scientific advances across the varying forms of social media on these developments? We look here to address these issues and to provide some suggestions for the problems that are currently emerging.

Robin Dehler, Oliver Schumann, Jona Ruof et al.

The integration of service-oriented architectures (SOA) with function offloading for distributed, intelligent transportation systems (ITS) offers the opportunity for connected autonomous vehicles (CAVs) to extend their locally available services. One major goal of offloading a subset of functions in the processing chain of a CAV to remote devices is to reduce the overall computational complexity on the CAV. The extension of using remote services, however, requires careful safety analysis, since the remotely created data are corrupted more easily, e.g., through an attacker on the remote device or by intercepting the wireless transmission. To tackle this problem, we first analyze the concept of SOA for distributed environments. From this, we derive a safety framework that validates the reliability of remote services and the data received locally. Since it is possible for the autonomous driving task to offload multiple different services, we propose a specific multi-staged framework for safety analysis dependent on the service composition of local and remote services. For efficiency reasons, we directly include the multi-staged framework for safety analysis in our service-oriented function offloading framework (SOFOF) that we have proposed in earlier work. The evaluation compares the performance of the extended framework considering computational complexity, with energy savings being a major motivation for function offloading, and its capability to detect data from corrupted remote services.

Vincent van Vliet, Menno van den Hout, Kadir Gümüş et al.

We present a 19-day joint measurement of optical turbulence and coherent data communications over a 4.6 km urban FSO link, providing empirical insights into turbulence effects on the performance of fiber-coupled coherent communication systems.

Fabio Arena, G. Pau, A. Severino

Road safety is an active area of research for the automotive industry, and certainly one of ongoing interest to governments around the world. The intelligent transportation system (ITS) is one of several viable solutions with which to improve road safety, where the communication medium (e.g., among vehicles and between vehicles and the other components in an ITS environment, such as roadside infrastructure) is typically wireless. A typical communication standard adopted by car manufacturers is IEEE 802.11p for communications. Thus, this paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting. Specifically, we analyze both MAC and PHY layers in a dedicated short-range communication (DSRC) environment.

Wanting Yang, Z. Liew, Wei Yang Bryan Lim et al.

The development of emerging applications, such as autonomous transportation systems, is expected to result in an explosive growth in mobile data traffic. As the available spectrum resource becomes more and more scarce, there is a growing need for a paradigm shift from Shannon's Classical Information Theory (CIT) to semantic communication (SemCom). Specifically, the former adopts a “transmit-before-understanding” approach while the latter leverages artificial intelligence (AI) techniques to “understand-before-transmit,” thereby alleviating bandwidth pressure by reducing the amount of data to be exchanged without negating the semantic effectiveness of the transmitted symbols. However, the semantic extraction (SE) procedure incurs costly computation and storage overheads. In this article, we introduce an edge-driven training, maintenance, and execution of SE. We further investigate how edge intelligence can be enhanced with SemCom through improving the generalization capabilities of intelligent agents at lower computation overheads and reducing the communication overhead of information exchange. Finally, we present a case study involving semantic-aware resource optimization for the wireless powered Internet of Things (IoT).

Abdallah Moubayed, A. Shami, Parisa Heidari et al.

Vehicle-to-everything (V2X) communication and services have been garnering significant interest from different stakeholders as part of future intelligent transportation systems (ITSs). This is due to the many benefits they offer. However, many of these services have stringent performance requirements, particularly in terms of the delay/latency. Multi-access/mobile edge computing (MEC) has been proposed as a potential solution for such services by bringing them closer to vehicles. Yet, this introduces a new set of challenges such as where to place these V2X services, especially given the limit computation resources available at edge nodes. To that end, this work formulates the problem of optimal V2X service placement (OVSP) in a hybrid core/edge environment as a binary integer linear programming problem. To the best of our knowledge, no previous work considered the V2X service placement problem while taking into consideration the computational resource availability at the nodes. Moreover, a low-complexity greedy-based heuristic algorithm named “Greedy V2X Service Placement Algorithm” (G-VSPA) was developed to solve this problem. Simulation results show that the OVSP model successfully guarantees and maintains the QoS requirements of all the different V2X services. Additionally, it is observed that the proposed G-VSPA algorithm achieves close to optimal performance while having lower complexity.

Xuefeng Fan, Gang Shan, Jianwei Fan et al.

The long-term durability of SBS–nano TiO2 composite modified asphalt and mixtures is affected by repetitive aging and regeneration, which alter their mechanical and environmental performance. Understanding these changes is critical for improving the recycling and reuse of modified asphalt in pavement engineering. In this study, SBS–nano TiO2 composite modified asphalt underwent primary aging, primary regeneration, secondary aging, and secondary regeneration. Micro-scale tests, including gel permeation chromatography (GPC) and scanning electron microscopy (SEM), were conducted to assess morphological and molecular weight changes. Macro-scale performance tests, including dynamic shear rheometer (DSR), bending beam rheometer (BBR), rutting, bending, Marshall stability, splitting strength, and dynamic modulus tests, were used to evaluate high- and low-temperature properties, moisture resistance, and fatigue resistance. The results showed that repeated aging caused SBS degradation, reducing its molecular weight, while oxidation of asphalt components increased their molecular weight. In regenerated asphalt, aged and cracked SBS chains interwove with newly added chains, whereas nano-TiO2 remained stable throughout aging and regeneration. High-temperature performance of asphalt and mixtures was significantly enhanced after aging, but low-temperature properties and fatigue resistance deteriorated. Regeneration partially restored these properties, though not to the level of the original material. Moisture resistance remained generally stable, with freeze–thaw splitting strength ratio decreasing by 3.3%–4.1%. The dynamic modulus increased with aging but declined after regeneration, while fatigue resistance showed the opposite trend. Overall, SBS–nano TiO2 composite modified asphalt and mixtures exhibit superior high-temperature performance compared to the original material after repeated aging and regeneration. However, their low-temperature and fatigue properties decline progressively. Regeneration mitigates but cannot fully reverse these effects. These findings provide a performance basis for the repeated recycling of composite modified asphalt and highlight the need for strategies that better restore low-temperature and fatigue performance during regeneration.

Guixi Guo, Lei Wan, Deming Zhang et al.

Tunnel excavation typically induces disturbance to the surrounding soil. Advance grouting using small-diameter pipes can effectively mitigate surface settlement. Taking the mine-method tunnel at the southern end of Xiancun Station on Guangzhou Rail Transit Line 18 as the research object, this paper uses the Midas GTS NX three-dimensional finite element (FE) software and adopts the upper-lower excavation method that prioritizes the formation of an upper support closed loop to simulate and analyze the impact of the CRD method on tunnel excavation under different grouting layer thicknesses. The research indicates that the surface settlement curve exhibits a “U”-shape. The settlement value decreases as the thickness of the grouting layer increases; when the thickness increases from 1.2 m to 2.0 m, the maximum surface settlement decreases from 12.87 mm to 9.09 mm, with successive reductions of 1.30 mm, 1.11 mm, 0.81 mm, and 0.56 mm, corresponding to rates of 10.10%, 9.59%, 7.67%, and 5.6%. Increasing the thickness of the grouting layer can effectively control surface settlement; however, when the thickness reaches 2.0 m, the stress distribution undergoes a change. Specifically, the compressive stress at the arch waist increases to 1683.01 kPa, and plastic failure occurs in the surrounding rock. By comparing the numerical results with field monitoring data, it is determined that when the grouting layer thickness is 1.4 m and the elastic modulus is increased by 30% based on that of the upper-soft soil, the model prediction shows the highest consistency with the actual effect. Furthermore, it is suggested that the grouting layer thickness be increased to 1.6 m. This study delivers a scientific foundation for the design of grouting parameters and the optimization of construction schemes for tunnels in composite strata and is of importance to improving tunnel construction technology in underground rail transit.

Kristi Dulaj, Abdulraqeb Alhammadi, Ibraheem Shayea et al.

A revolutionary age in telecommunications is being ushered in by the confluence of machine learning (ML) with fifth-generation (5G) wireless communication technologies and beyond. This research investigates ML approaches in 5G networks for adaptive spectrum usage, quality of service (QoS) management, predictive maintenance, and network optimization. By leveraging ML algorithms, 5G networks can forecast user behavior, allocate resources optimally, and dynamically adjust to changing conditions, enhancing performance and dependability. Additionally, ML-driven methods improve cybersecurity in 5G settings. Furthermore, the integration of ML in 5G networks is pivotal for advancing intelligent transportation systems, enabling dynamic route optimization, adaptive traffic management, and enhanced vehicular communication. Intelligent networks will transform wireless communication by replacing traditional processing with end-to-end solutions, utilizing cognitive radio systems and deep reinforcement learning for optimized spectrum sharing and efficiency. Despite significant potential, challenges such as interoperability, security, scalability, and energy efficiency must be addressed. This paper discusses these challenges and highlights future trends beyond 5G, emphasizing ML's critical role in shaping the future of wireless communication systems.

Rizwan Abbas, Gehad Abdullah Amran, Irshad Hussain et al.

The journal retracts the article titled “A Soft Computing View for the Scientific Categorization of Vegetable Supply Chain Issues” [...]

Amal Yousseef, Yu-Zheng Lin, Shalaka Satam et al.

Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, AV architectures' increasing connectivity and complexity have introduced significant cybersecurity risks. This survey provides a comprehensive review of AV security challenges, focusing on widely adopted threat modeling frameworks such as STRIDE, DREAD, andMITRE ATT&CK. By examining common attack vectors and real-world case studies, including the Jeep Cherokee and Tesla Model S exploits, we highlight the urgent need for robust cybersecurity in in-vehicle systems and external interfaces. To complement existing modeling practices, we introduce Hybrid-SCDM, a novel framework that combines STRIDE-based threat classification with CVSS-derived DREAD scoring. This model transforms qualitative threat identification into quantitative risk prioritization by mapping CVSS metrics to DREAD dimensions through normalization. Applied to a generic multi-layered AV architecture, our findings show that intra-vehicle networks, especially CAN bus spoofing and fuzzing attacks, and suspension attacks, represent the most critical vulnerabilities due to their high exploitability and systemic impact. Beyond technical modeling, the survey explores emerging defense mechanisms such as blockchain-enabled Vehicle-to-Everything (V2X) communication, AI-driven anomaly detection, and secure Over-The-Air (OTA) updates. We also examine legal and ethical considerations surrounding data privacy, user safety, and regulatory compliance. By integrating analytical modeling with broad system insights, this work provides actionable recommendations for advancing the cybersecurity posture of autonomous vehicles.

Alp Öktem, Farida Boudichat

This paper presents Awal, a community-powered initiative for developing language technology resources for Tamazight. We provide a comprehensive review of the NLP landscape for Tamazight, examining recent progress in computational resources, and the emergence of community-driven approaches to address persistent data scarcity. Launched in 2024, awaldigital.org platform addresses the underrepresentation of Tamazight in digital spaces through a collaborative platform enabling speakers to contribute translation and voice data. We analyze 18 months of community engagement, revealing significant barriers to participation including limited confidence in written Tamazight and ongoing standardization challenges. Despite widespread positive reception, actual data contribution remained concentrated among linguists and activists. The modest scale of community contributions -- 6,421 translation pairs and 3 hours of speech data -- highlights the limitations of applying standard crowdsourcing approaches to languages with complex sociolinguistic contexts. We are working on improved open-source MT models using the collected data.

A. Tarik Leblebici, Sumeyra Hassan, Erdal Panayirci et al.

This paper proposes a joint communication and indoor positioning (JCP) system based on visible light communication (VLC) designed for high-precision indoor environments. The framework supports 2D and 3D positioning using received signal strength (RSS) from pilot transmissions, enhanced by the radical axis theorem to improve accuracy under measurement uncertainties. Communication is achieved using spatial modulation (SM) with M-ary pulse amplitude modulation (PAM), where data is conveyed through the modulation symbol and the active light-emitting diode (LED) index, improving spectral efficiency while maintaining low complexity. A pilot-aided least squares (LS) estimator is employed for joint channel and dimming coefficient estimation, enabling robust symbol detection in multipath environments characterized by both line-of-sight (LOS) and diffuse non-line-of-sight (NLOS) components, modeled using Rician fading. The proposed system incorporates a dimming control mechanism to meet lighting requirements while maintaining reliable communication and positioning performance. Simulation results demonstrate sub-centimeter localization accuracy at high signal-to-noise ratios (SNRs) and bit error rates (BERs) below 10^{-6} for low-order PAM schemes. Additionally, comparative analysis across user locations reveals that positioning and communication performance improve significantly near the geometric center of the LED layout. These findings validate the effectiveness of the proposed system for future 6G indoor networks requiring integrated localization and communication under practical channel conditions.

Ahmed Al-Hilo, M. Samir, C. Assi et al.

Unmanned Aerial Vehicles (UAVs) are gaining growing interests due to the paramount roles they play, particularly these days, in enabling new services that help modernize our transportation, supply chain, search and rescue, among others. They are capable of positively influencing wireless systems through enabling and fostering emerging technologies such as autonomous driving, vertical industries, virtual reality and so many others. The Internet of Vehicles is a prime sector benefiting from the services offered by future cellular systems in general and UAVs in particular, and this paper considers the problem of content delivery to vehicles on road segments with either overloaded or no available communication infrastructure. Incoming vehicles demand service from a library of contents that is partially cached at the UAV; the content of the library is also assumed to change as new vehicles carrying more popular contents arrive. Each inbound vehicle makes a request and the UAV decides on its best trajectory to provide service while maximizing a certain operational utility. Given the energy limitation at the UAV, we seek an energy efficient solution. Hence, our problem consists of jointly finding caching decisions, UAV trajectory and radio resource allocation which is formulated mathematically as a Mixed Integer Non-Linear Problem (MINLP). However, owing to uncertainties in the environment (e.g., random arrival of vehicles, their requests for contents and their existing contents), it is often hard and impractical to solve using standard optimization techniques. To this end, we formulate our problem as a Markov Decision Process (MDP) and we resort to tools such as Proximal Policy Optimization (PPO), a very promising Reinforcement Learning method, along with a set of crafted algorithms to solve our problem. Finally, we conduct simulation-based experiments to analyze and demonstrate the superiority of our solution approach compared with four counterparts and baseline schemes.

Zaheda Sultana, C. H. Basha, M. M. Irfan

Electric vehicles (EV s) Significantly contribute to sustainable development goals (SDGs) by mitigating emissions, enhancing air quality, fostering renewable energy use, generating green employment, and facilitating access to sustainable transportation. In electric vehicles (EV s), multiple components require communication protocols to enable synchronization of subsystems such as battery management and charging infrastructure and ensure optimal efficiency and interoperability. There is a wide adoption of Electric vehicles (EV s) worldwide to create a sustainable environment. Based upon the above aspects, this article presents a thorough literature review of the communication protocols for EV s, where the key technical components of the EV ecosystem are summarized in detail. Further, this study presented an overview of communication protocols for EV s, covering front- end and back-end protocols. The significance of protocols in EV charging is discussed, including aspects like interoperability, communication and data exchange, plug- and-charge capability, monitoring, and smart charging. The findings of the study conclude that this communication protocol is used to integrate electric vehicles (EVs) into transportation networks. Front-end and back-end protocols govern the communication between electric vehicles (EVs) and charging stations, as well as between the infrastructure and third-party operators. Protocols like ISO 15118, OCPP, IEC 61850, and others are used for different purposes. Protocols are based on their openness, compatibility, maturity, and market adoption to determine their adequacy for adoption in the EV business. The review's novelty comes from its comprehensive analysis of communication protocols for electric vehicles (EV s), which encompasses both detailed elements and performing outcomes.

Dong Chen, Kaixiang Zhang, Yongqiang Wang et al.

Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs is the so-called cooperative adaptive cruise control (CACC) where vehicles drive in platoons and cooperate to achieve safe and efficient transportation. In this study, we formulate CACC as a multi-agent reinforcement learning (MARL) problem. Diverging from existing MARL methods that use centralized training and decentralized execution which require not only a centralized communication mechanism but also dense inter-agent communication during training and online adaptation, we propose a fully decentralized MARL framework for enhanced efficiency and scalability. In addition, a quantization-based communication scheme is proposed to reduce the communication overhead without significantly degrading the control performance. This is achieved by employing randomized rounding numbers to quantize each piece of communicated information and only communicating non-zero components after quantization. Extensive experimentation in two distinct CACC settings reveals that the proposed MARL framework consistently achieves superior performance over several contemporary benchmarks in terms of both communication efficiency and control efficacy. In the appendix, we show that our proposed framework's applicability extends beyond CACC, showing promise for broader intelligent transportation systems with intricate action and state spaces.

Naufal Ghani Nurfaizi, Fauzan Romadlon

Abstract Food loss in the dairy supply chain is a challenge that impacts the production efficiency and sustainability of the livestock industry. This study aimed to analyze the effect of supply chain practices, including milking, inventory, transportation, and communication, on food loss in the dairy supply chain in Banyumas Regency, Indonesia. This study used a quantitative approach with multiple linear regression analysis based on data from 46 dairy farmers. The results showed that only transportation significantly affected food loss with a regression coefficient of -0.450 and a p value of 0.004. Poor road infrastructure, inefficient transportation, and inadequate delivery support equipment contributed to milk loss during distribution. Although milking, inventory, and communication did not show significant effects, these practices are still important in maintaining milk quality. Farmers are advised to improve milking hygiene, improve storage systems, and strengthen stakeholder coordination. The implications of this study indicate that reducing food loss can improve milk production efficiency, maintain supply stability, and support farmer welfare. Further studies are recommended to expand the research scope to cooperatives and processing industries to obtain a more comprehensive picture of the dairy supply chain. Keywords: Banyumas Regency, distribution efficiency, food loss, milk supply chain, transportation Abstrak Food loss dalam rantai pasok susu merupakan tantangan yang berdampak pada efisiensi produksi dan keberlanjutan industri peternakan. Penelitian ini bertujuan menganalisis pengaruh praktik rantai pasok, yang mencakup pemerahan, persediaan, transportasi, dan komunikasi, terhadap food loss dalam rantai pasok susu di Kabupaten Banyumas, Indonesia. Studi ini menggunakan pendekatan kuantitatif dengan analisis regresi linier berganda berdasarkan data dari 46 peternak sapi perah. Hasil penelitian menunjukkan bahwa hanya transportasi yang berpengaruh signifikan terhadap food loss dengan koefisien regresi -0,450 dan p value 0,004. Infrastruktur jalan yang buruk, ketidakefisienan alat transportasi, dan alat pendukung pengiriman yang kurang berkontribusi terhadap kehilangan susu selama distribusi. Meskipun pemerahan, persediaan, dan komunikasi tidak menunjukkan pengaruh signifikan, praktik-praktik ini tetap penting dalam menjaga kualitas susu. Peternak disarankan meningkatkan kebersihan pemerahan, memperbaiki sistem penyimpanan, dan memperkuat koordinasi antar pemangku kepentingan. Implikasi penelitian ini menunjukkan bahwa pengurangan food loss dapat meningkatkan efisiensi produksi susu, menjaga stabilitas pasokan, dan mendukung kesejahteraan peternak. Studi lanjutan disarankan untuk memperluas cakupan penelitian hingga ke koperasi dan industri pengolahan guna mendapatkan gambaran lebih menyeluruh tentang rantai pasok susu. Kata kunci: efisiensi distribusi, food loss, Kabupaten Banyumas, rantai pasok susu, transportasi

Pablo Emilio Mora Lozano, Jairo R. Montoya-Torres

<i>Background:</i> For several years, two of the major concerns of logistics managers are (i) the visibility of global supply chains and (ii) the uncertainty in deciding which existing logistics security program is the most appropriate according to the security levels for their organization. This last decision is needed to ensure traceability and visibility of the supply chain. The purpose of this paper is to present an analysis of the main public and private supply chain security management programs in Latin America and the Caribbean. <i>Methods:</i> A qualitative and quantitative research methodology based on thematic content analysis is followed. The four main existing security programs in Latin America and the Caribbean are systematically compared and a common general framework is developed. <i>Results:</i> The analysis shows a high degree of similarity between the levels of security contained in the selected programs. <i>Conclusions:</i> We found that there is little guidance available for companies interested in managing security risks in their supply chains through these logistics’ security programs. This article contributes to the literature on logistics security programs that is currently gaining momentum in managing security risks in global supply chains and provides academic insights into the choice and/or complementarity of one or more logistics security programs.

Xiao Zheng, Wenchi Cheng, Jingqing Wang et al.

Future wireless communications are promising to support ubiquitous connections and high data rates with cost-effective devices. Benefiting from the energy-efficient elements with low cost, reconfigurable intelligent surface (RIS) emerges as a potential solution to fulfill such demands, which has the capability to flexibly manipulate the wireless signals with a tunable phase. Recently, as the operational frequency ascends to the sub-terahertz (THz) bands or higher bands for wireless communications in six-generation (6G), it becomes imperative to consider the near-field propagation in RIS-assisted communications. The challenging acquisition of channel parameters is an inherent issue for near-field RIS-assisted communications, where the complex design is essential to acquire the informative near-field channel embedded with both the angle and distance information. Hence, in this paper we systematically investigate the potential of exploiting location information for near-field RIS-assisted communications. Firstly, we present the progresses in the near-field RIS-assisted communications, which are compatible with existing wireless communications and show the potential to achieve the fine-grained localization accuracy to support location-driven scheme. Then, the Fresnel zone based model is introduced, with which the location-driven beamforming scheme and corresponding frame structure are developed. Also, we elaborate on four unique advantages for leveraging location information in RIS-assisted communications, followed by numerical simulations. Finally, several key challenges and corresponding potential solutions are pointed out.