Hasil untuk "Transportation and communications"

Maria-Garyfallio Volakaki, Grigorios Papaioannou, Demosthenes Vouyioukas

This paper introduces a coordinated framework in which a base station (BS) and a Reconfigurable Intelligent Surfaces (RIS) jointly support their respective user groups while mitigating the impact of a Uncrewed Aerial Vehicle (UAV)-based jammer. Specifically, the RIS-assisted users rely on a reflective surface under attack from an UAV-jammer, and the BS simultaneously supports its own associated UEs alongside the RIS. We adopt an alternating optimization strategy that decomposes the original non-convex formulation into tractable subproblems using Block Coordinate Descent (BCD), thereby enabling multi-tier cooperation in complex interference environments. We frame our objective as the sum rate maximization, a metric for overall system performance, to maintain service quality and enhance robustness under severe jamming. The core of our methodology is the transformation of the resulting non-convex subproblems into tractable convex formulations via Semidefinite Programming (SDP). We employ a joint design of beamforming and phase shift optimization, whose combined effect leads to substantial performance improvements within the proposed framework. Extensive simulations and comparisons with existing algorithms demonstrate that this design achieves superior interference suppression and resource efficiency, significantly outperforming state-of-the-art baselines in sum rate, energy efficiency, UAV-jamming resilience and group-aware support for both BS- and RIS-served users.

Anum Ali, Nuria González-Prelcic, Robert W. Heath

Seyed Hamed Seyed Matin, Ali Abdi Kordani

Lane-changing behavior can significantly affect many aspects of traffic flow including capacity, shock waves, and safety. Therefore, it is imperative to understand the determinants behind lane change behavior. This paper investigates the determinants of lane-changing in congested traffic using video-recording as well as a survey approach. A mixed logit model was estimated to account for unobserved heterogeneity in lane-changing behavior across drivers. Estimation results show that all categories of explanatory variables including socioeconomic, driving style, and road environment have a significant effect on lane changing behavior. Besides, unobserved heterogeneity and taste variation among drivers with regards to the lateral distance of the target vehicle from the left car has been observed. Among the non-random parameters, speed of target vehicle, being a law-evading driver, disregarding yellow traffic signals at intersections, lateral distance of target vehicle from right/left cars, and experiencing at least two accidents are positively associated with a higher likelihood of lane changing when a driver encounters a downstream queue. The aforementioned interesting findings can significantly help to improve the performance of traffic flow models for the purpose of replicating and predicting traffic flow.

Branislav Šarkan, Jacek Caban, Arkadiusz Małek et al.

The article contains an analysis of power generation by a photovoltaic system with a peak power of 3 MWp and a wind turbine with a power of 3.45 MW. The acquired time series of generated power was analyzed using traditional and modern analytical methods. The power generated by these two Renewable Energy Sources was characterized separately and then by their mix. In this article, the power signature was defined as the power generated by the photovoltaic system and the wind turbine in the state space over a period of one month. The state space was extracted from the results of cluster analysis. The experiment with clustering was carried out into 10 classes. The K-Means clustering algorithm was used to determine the clusters in a variant without prior labeling of classes with the method of learning without the participation of the teacher. In this way, the trajectories of the power generation process from two Renewable Energy Sources were determined in the 10-state space. Knowing which class each data record belongs to, the frequencies of staying in each state were determined. The computational algorithm presented in the article may have great practical application in balancing the power grid powered by energy produced from renewable sources.

Saki Rezwana, Mohammad Razaur Rahman Shaon, Nicholas Lownes et al.

he advent of autonomous technologies necessitates a deeper understanding of pedestrian behavior and safety in environments where pedestrians need to interact with driverless vehicles (DV). Our study explores how pedestrians perceive and react to DVs compared with Human-Driven Vehicles (HDV), focusing on objective measures such as gap acceptance (GA) and psychophysiological indicators like Electro-dermal Activity (EDA). Structured in three phases, the study comprises a preliminary questionnaire to gauge public perception, followed by immersive virtual reality (VR) simulations that mimic real-world traffic scenarios within a VR environment, and concludes with a post-experiment survey. The simulation experiment was designed to analyze pedestrian responses to varying traffic scenarios developed using DVs and HDVs, measuring EDA to assess emotional and stress responses leading to changes in the gap acceptance behavior. The study employed hypothesis testing to assess DV's impact on pedestrians' psychophysiological reactions that can lead to changes in pedestrian behavior. This study also explored the effect of education level and perception of pedestrians towards automation technology that may influence outcomes. The analysis of EDA showed higher stress levels in scenarios involving DVs measured using the Galvanic Skin Response component. This result heightened stress response may be attributed to the unpredictability and novelty of DVs. The analysis with gap acceptance (GA) time revealed significant differences in GA times across traffic scenarios. Pedestrians exhibited longer GA times with DVs than HDVs, suggesting cautious crossing behavior. Our results underscore the impact of traffic scenarios on pedestrian behavior and stress levels, highlighting the influence of driverless technology on pedestrian dynamics.

Yang Li, Xinyu Zhou, Jun Zhao

Semantic communication is a new paradigm that aims at providing more efficient communication for the next-generation wireless network. It focuses on transmitting extracted, meaningful information instead of the raw data. However, deep learning-enabled image semantic communication models often require a significant amount of time and energy for training, which is unacceptable, especially for mobile devices. To solve this challenge, our paper first introduces a distributed image semantic communication system where the base station and local devices will collaboratively train the models for uplink communication. Furthermore, we formulate a joint optimization problem to balance time and energy consumption on the local devices during training while ensuring effective model performance. An adaptable resource allocation algorithm is proposed to meet requirements under different scenarios, and its time complexity, solution quality, and convergence are thoroughly analyzed. Experimental results demonstrate the superiority of our algorithm in resource allocation optimization against existing benchmarks and discuss its impact on the performance of image semantic communication systems.

Takayuki Kishii

This study was conducted in 2007–2009 as the IATSS Research Project to consider the comfort and safety of city centers in the automobile age from the perspective of “parking places.”We focused on four elements related to parking places, that is, 3D & M (density, disposition, design, and management) and proposed changes to parking policy in Japan by comparing and analyzing the actual conditions of parking lots or facilities in different city centers and legal systems in several counties, including Japan, the United States of America, the United Kingdom, and Germany.The key concept of our proposal is that we should shift the policy of parking from equipment-duty car-parking “on-site” to parking installation”in-area,“good management, and smart operation.The findings of this project were widely shared through open symposium with non-members of the IATSS as well as book publication and led to many system revisions in the Japanese parking policies.

Bo Fu, Huanxing Zhou, Fei Ye et al.

The crystalline blockage of tunnel drainage pipes poses a common challenge to tunnel engineering, particularly in regions with abundant groundwater and severe ion erosion. Based on the design of concrete mix proportion, this paper improves the calcium ion erosion resistance of shotcrete by adding permeable crystalline sodium methyl silicate waterproofing agent and silane waterproofing agent. Concurrently, the mechanical properties and microscopic characterization of waterproofing agent concrete are carried to determine the optimal dosage for practical engineering applications. The experimental results reveal that the sodium methyl silicate waterproofing agent has minimal impact on the calcium ion dissolution resistance of shotcrete. In contrast, the silane waterproofing agent significantly enhances the calcium dissolution performance of shotcrete, and the optimum dosage is identified as 0.4%. During long-term maintenance, the silane waterproofing agent proves more effective in improving the compressive strength of shotcrete compared to the sodium methyl silicate waterproofing agent, showing an increase rate exceeding 20%. Both waterproofing agents contribute to the enhancement of the tensile strength of shotcrete, and the enhancement effect is consistent with the compressive strength. The permeable crystalline waterproofing agent expedites the cement hydration process, resulting in the formation of higher-density calcium silicate hydrates (C-S-H) gel and ettringite (AFt). These substances fill the pores of shotcrete leading to a more compact internal structure. The calcium ion dissolution and mechanical strength test results collectively validate the superior effectiveness crystallization prevention of aterproofing agents . This research provides valuable insights for addressing the tunnel crystallization phenomenon caused by the calcium dissolution.

Editorial Office

No abstract available.

Yuanwei Liu, Chongjun Ouyang, Zhaolin Wang et al.

Multiple-antenna technologies are evolving towards larger aperture sizes, extremely high frequencies, and innovative antenna types. This evolution is fostering the emergence of near-field communications (NFC) in future wireless systems. Considerable attention has been directed towards this cutting-edge technology due to its potential to enhance the capacity of wireless networks by introducing increased spatial degrees of freedom (DoFs) in the range domain. Within this context, a comprehensive review of the state of the art on NFC is presented, with a specific focus on its 1) fundamental operating principles, 2) channel modeling, 3) performance analysis, 4) signal processing techniques, and 5) integration with other emerging applications. Specifically, 1) the basic principles of NFC are characterized from both physics and communications perspectives, unveiling its unique properties in contrast to far-field communications. 2) Building on these principles, deterministic and stochastic near-field channel models are explored for spatially-discrete (SPD) and continuous-aperture (CAP) arrays. 3) Based on these models, existing contributions to near-field performance analysis are reviewed in terms of DoFs/effective DoFs (EDoFs), the power scaling law, and transmission rate. 4) Existing signal processing techniques for NFC are systematically surveyed, which include channel estimation, beamforming design, and low-complexity beam training. 5) Major issues and research opportunities in incorporating near-field models into other promising technologies are identified to advance NFC's deployment in next-generation networks. Throughout this paper, promising directions are highlighted to inspire future research endeavors in the realm of NFC, underscoring its significance in the advancement of wireless communication technologies.

Ryuhei Hibi, Hiroaki Hashida, Yuichi Kawamoto et al.

Intelligent reflecting surfaces (IRSs) are gaining attention as a low-cost solution to the coverage reduction in high-frequency bands used in next-generation communications. IRSs achieve low costs by controlling only the reflection of radio waves. However, to improve further the propagation environment, larger IRS sizes are required owing to their inability to amplify and retransmit signals. As the IRS size increases, the near-field region expands, requiring beamfocusing instead of beamforming, which is extensively used in existing research. This results in considerable overhead for IRS control decisions. To address this, constructing a codebook that achieves high communication quality with fewer IRS control patterns is effective. This article presents experimental results demonstrating the effectiveness of beamfocusing, construction policy for nonuniform three-dimensional codebooks, and simulation evaluation results of communication performance when operating IRSs with various codebooks. We believe these insights will foster further value for IRSs in next-generation communications.

Zehra Yigit, Ertugrul Basar

Integrated sensing and communication (ISAC) is recognized as one of the key enabling technologies for sixth-generation (6G) wireless communication networks, facilitating diverse emerging applications and services in an energy and cost-efficient manner. This paper proposes a multi-user multi-target ISAC system to enable full-space coverage for communication and sensing tasks. The proposed system employs a hybrid simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) comprising active transmissive and passive reflective elements. In the proposed scheme, the passive reflective elements support communication and sensing links for local communication users and sensing targets situated within the same physical region as the base station (BS), while low-power active transmissive elements are deployed to improve sensing performance and overcome high path attenuation due to multi-hop transmission for distant communication users and sensing targets situated far from of the coverage area of the BS. Moreover, to optimize the transmissive/reflective coefficients of the hybrid STAR-RIS, a semi-definite relaxation (SDR)-based algorithm is proposed. Furthermore, to evaluate communication and sensing performance, signal-to-interference-noise ratio (SINR) and Cramer-Rao bound (CRB) metrics have been derived and investigated via conducting extensive computer simulations.

Shuying Lin, Yulong Zou, Yuhan Jiang et al.

This paper investigates a wireless network consisting of an unmanned aerial vehicle (UAV) base station (BS), a fully-connected reconfigurable intelligent surface (FC-RIS), and multiple users, where the downlink signal can simultaneously be captured by an aerial eavesdropper at a random location. To improve the physical-layer security (PLS) of the considered downlink multiuser communications, we propose the fully-connected reconfigurable intelligent surface aided round-robin scheduling (FCR-RS) and the FC-RIS and ground channel state information (CSI) aided proportional fair scheduling (FCR-GCSI-PFS) schemes. Thereafter, we derive closed-form expressions of the zero secrecy rate probability (ZSRP). Numerical results not only validate the closed-form ZSRP analysis, but also verify that the proposed GCSI-PFS scheme obtains the same performance gain as the full-CSI-aided PFS in FC-RIS-aided communications. Furthermore, optimizing the hovering altitude remarkably enhances the PLS of the FC-RIS and UAV empowered multiuser communications.

Feilong Wang, Xin Wang, Xuegang Ban

Emerging technologies drive the ongoing transformation of Intelligent Transportation Systems (ITS). This transformation has given rise to cybersecurity concerns, among which data poisoning attack emerges as a new threat as ITS increasingly relies on data. In data poisoning attacks, attackers inject malicious perturbations into datasets, potentially leading to inaccurate results in offline learning and real-time decision-making processes. This paper concentrates on data poisoning attack models against ITS. We identify the main ITS data sources vulnerable to poisoning attacks and application scenarios that enable staging such attacks. A general framework is developed following rigorous study process from cybersecurity but also considering specific ITS application needs. Data poisoning attacks against ITS are reviewed and categorized following the framework. We then discuss the current limitations of these attack models and the future research directions. Our work can serve as a guideline to better understand the threat of data poisoning attacks against ITS applications, while also giving a perspective on the future development of trustworthy ITS.

Ahmet M. Elbir, Abdulkadir Celik, Ahmed M. Eltawil

Integrated sensing and communications (ISAC) has emerged as a means to efficiently utilize spectrum and thereby save cost and power. At the higher end of the spectrum, ISAC systems operate at wideband using large antenna arrays to meet the stringent demands for high-resolution sensing and enhanced communications capacity. On the other hand, the overall design should satisfy energy-efficiency and hardware constraints such as operating on low resolution components for a practical scenario. Therefore, this paper presents the design of Hybrid ANalog and Digital BeAmformers with Low resoLution (HANDBALL) digital-to-analog converters (DACs). We introduce a greedy-search-based approach to design the analog beamformers for multi-user multi-target ISAC scenario. Then, the quantization distortion is taken into account in order to design the baseband beamformer with low resolution DACs. We evaluated performance of the proposed HANDBALL technique in terms of both spectral efficiency and sensing beampattern, providing a satisfactory sensing and communication performance for both one-bit and few-bit designs.

Ali Bemani, Nassar Ksairi, Marios Kountouris

Integrated sensing and communications (ISAC) is regarded as a key technology in next-generation (6G) mobile communication systems. Affine frequency division multiplexing (AFDM) is a recently proposed waveform that achieves optimal diversity gain in high mobility scenarios and has appealing properties in high-frequency communication. In this letter, we present an AFDM-based ISAC system. We first show that in order to identify all delay and Doppler components associated with the propagation medium, either the full AFDM signal or only its pilot part consisting of one discrete affine Fourier transform (DAFT) domain symbol and its guard interval can be used. Our results show that using one pilot symbol achieves almost the same sensing performance as using the entire AFDM frame. Furthermore, due to the chirp nature of AFDM, sensing with one pilot provides a unique feature allowing for simple self-interference cancellation, thus avoiding the need for expensive full duplex methods.

Ruchi Singhal, Apurvkumar Desai, Chetan R. Patel

Since the electrical vehicles (EVs) are infrastructure-dependent technology, their penetration faces the problem of lacking recharging infrastructure. Thus, there is a dilemma of chicken-egg in the penetration of EVs and their charging infrastructure for the decision-makers. The article examines the e-mobility scenario of 3 Indian cities to understand issues and challenges in implementing EVs. The study suggests a co-diffusion strategy for the EVs and charging infrastructure. Firstly, the priority EV segment has been decided based on the transport mode preference. Then, suitability of charging facilities according to the segment of the EVs has been presented by analyzing the turnover rate and time spent at several places. The study recommends policies on the upfront cost of EVs, charging infrastructure, awareness generation and others, while leveraging the existing government schemes like Atmanirbhar Bharat and FAME-II.

Lukas Hacker, Jorg Seewig

Deep Neural Networks (DNNs) are used in various domains and industry fields with great success due to their ability to learn complex tasks from high-dimensional data. However, the data-driven approach within deep learning results in various DNN-specific insufficiencies (e.g., robustness limitations, overconfidence, lack of interpretability), which makes the usage in safety-critical applications, like automated driving, challenging. An important safety strategy to address these limitations is the detection of DNN errors (e.g., false positives) during runtime. In this work, we present a general error detection approach for DNNs, which combines diverse monitoring methods to address different safety-related DNN insufficiencies simultaneously. To ensure consistency with the automotive safety domain, we take into account established concepts of the automotive safety standard ISO 21448 (SOTIF). We apply our error detection method on the safety-related use case of traffic sign recognition by using self-created 3D driving scenarios. In doing so, we consider different types of DNN errors related to in distribution, out of distribution, and adversarial data. We demonstrate that our approach is able to handle all these error types. Furthermore, we show the performance benefit of our method compared to a baseline DNN and to state of the art DNN monitoring methods.

Xiang Shen, Dajun Yuan, Dalong Jin et al.

Abstract Based on a cross-river tunnel of Wuhan Metro Line 8, we present a two-dimensional discrete element model for shield attitude adjustment considering the effect of overbreak cutters. The shield shell mechanics under the influence of over-excavation rate, over-excavation orientations, and overburden load are simulated, and the tunneling mechanics law and the ultimate range during the adjustment of the shield attitude are investigated. The simulation results indicate the following: (1) The greater the over-excavation rate, the smaller the force exerted by the soil layer in the negative direction of the shield movement; therefore, increasing the over-excavation rate is helpful in expanding the range of shield attitude adjustment. (2) The shield is stressed symmetrically while conducting positive and negative horizontal adjustments in the soil layer, which has a symmetrical distribution, but vertical upward adjustment is more difficult than vertical downward adjustment. (3) With the increase in overburden load, the space of the shield attitude adjustment is gradually reduced at the same over-excavation rate. A good engineering application was achieved in this project using the simulation model. It is recommended to use the attitude adjustment method by controlling the tunneling parameters. In difficult situations such as high overlying loads, the over-excavation cutter can be used to assist in adjusting the shield attitude.

Seyed Ali Haji Esmaeili, Ahmad Sobhani, Sajad Ebrahimi et al.

<i>Background</i>: Due to the growing demand for energy and environmental issues related to using fossil fuels, it is becoming tremendously important to find alternative energy sources. Bioethanol produced from switchgrass is considered as one of the best alternatives to fossil fuels. <i>Methods</i>: This study develops a two-stage supply chain modeling approach that first determines feasible locations for constructing switchgrass-based biorefineries in the state of North Dakota by using Geographic Information Systems (GIS) analysis. In the second stage, the profit of the corresponding switchgrass-based bioethanol supply chain is maximized by developing a mixed-integer linear program that aims to commercialize the bioethanol production while impacts of energy use and carbon emission costs on the supply chain decisions and siting of biorefineries are included. <i>Results</i>: The numerical results show that carbon emissions and energy consumption penalties affect optimal biorefinery selections and supply chain decisions. <i>Conclusions</i>: We conclude that there is no need to penalize both emissions and energy use simultaneously to achieve desirable environmental benefits, otherwise, the supply chain becomes non-profitable. Moreover, imposing emissions or energy consumption penalties makes the optimization model closer to supply sources while having higher land rental costs. Such policies would promote sustainable second-generation biomass production, thus decreasing reliance on fossil fuels.