IEEE Open Journal of Vehicular Technology最新文献

{"title":"A Fallback Localization Algorithm for Automated Vehicles Based on Object Detection and Tracking","authors":"Mario Rodríguez-Arozamena;Jose Matute;Javier Araluce;Lukas Kuschnig;Christoph Pilz;Markus Schratter;Joshué Pérez Rastelli;Asier Zubizarreta","doi":"10.1109/OJVT.2025.3560198","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3560198","url":null,"abstract":"Integrating Automated Vehicles (AVs) into everyday traffic is an ongoing challenge. Ensuring the safety of all involved agents, even in the presence of system failures, is crucial, especially in urban environments. This paper introduces a fallback-oriented localization algorithm for AVs designed to operate during main localization source failures. The method leverages stationary vehicles as dynamic landmarks, identified through the perception module, despite their initially unknown positions. By tracking relative positions before failure and applying trilateration, the algorithm estimates the ego vehicle's position. The proposed algorithm is evaluated through simulations, a real-world dataset, and practical tests on two vehicle models. The results include an average trajectory error of 0.62 m and 1.58 deg compared to the ground truth over different fallback maneuvers. This translates into an average relative translational error of 1.65% and a relative rotational error of 0.05 deg/m, improving the performance of an IMU-based dead reckoning and, hence, providing localization for performing safe stop maneuvers.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1085-1099"},"PeriodicalIF":5.3,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10963758","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Analysis of Sensing-Assisted Communications in Aerial-to-Ground Networks","authors":"Petros S. Bithas;Athanasios G. Kanatas;Konstantinos Maliatsos","doi":"10.1109/OJVT.2025.3559698","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3559698","url":null,"abstract":"Joint communication and sensing (JCAS) technology allows the coexistence of sensing and communication capabilities within the same frequency band without causing mutual interference. Aerial-to-ground wireless communication networks offer additional flexibility for communication users and sensing targets through the dynamic positioning of uncrewed aerial vehicles (UAVs), resulting in an extra degree of freedom to alleviate the challenges imposed by the dynamic characteristics of the wireless propagation channel. In this paper, the performance of a sensing-assisted aerial communication network is analytically investigated in scenarios with realistic assumptions for the channel and system model. Indeed, the presented analysis considers independent but non-identically distributed shadowing effects, non-isotropic antennas, and a generic statistical distribution for the radar cross section of sensing targets. Analytical expressions are derived for the statistics of the received signal-to-interference plus noise ratio (SINR), for both sensing and communication functionalities, while simpler expressions for special cases and asymptotic results are also obtained. Based on the analytical derivations, communication and sensing performance have been evaluated using, respectively, the outage and coverage probabilities and the ergodic radar estimation rate and detection probability. Numerical and simulation results demonstrate the accuracy of the proposed analysis and reveal how factors like non-identical distributed statistics of shadowing, small scale fading, and interference influence the performance of the system.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1140-1151"},"PeriodicalIF":5.3,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10960654","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart Electric Vehicle Charging Algorithm to Reduce the Impact on Power Grids: A Reinforcement Learning Based Methodology","authors":"Federico Rossi;Cesar Diaz-Londono;Yang Li;Changfu Zou;Giambattista Gruosso","doi":"10.1109/OJVT.2025.3559237","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3559237","url":null,"abstract":"The increasing penetration of electric vehicles (EVs) presents a significant challenge for power grid management, particularly in maintaining network stability and optimizing energy costs. Existing model predictive control (MPC)-based approaches for EV charging and discharging scheduling often struggle to balance computational efficiency with real-time operationability. This gap highlights the need for more advanced methods that can effectively mitigate the impact of EV activities on power grids without oversimplifying system dynamics. Here, we propose a novel scheduling methodology using a pre-trained Reinforcement Learning (RL) framework to address this challenge. The method integrates real grid simulations to monitor critical electrical points and variables while simplifying analysis by excluding the influence of real grid dynamics. The proposed approach formulates the scheduling problem to minimize costs, maximize rewards from ancillary service delivery, and mitigate network overloads at specified grid nodes. The methodology is validated on a benchmark electric grid, where realistic charging station utilization scenarios are simulated. The results demonstrate the method's robustness and ability to efficiently cope with the EV smart scheduling problem.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1072-1084"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10960355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Temporal Convolutional Network Framework for Intrusion Detection in Electric Vehicle Charging Stations","authors":"Ikram Benfarhat;Vik Tor Goh;Chun Lim Siow;It Ee Lee;Muhammad Sheraz;Eng Eng Ngu;Teong Chee Chuah","doi":"10.1109/OJVT.2025.3559421","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3559421","url":null,"abstract":"Electric Vehicle Charging Station (EVCS) systems have become increasingly critical to the energy and transportation sectors. The detection of various attacks in EVCS, including data interception in the Open Charge Point Protocol (OCPP), poses substantial cybersecurity challenges that existing deep learning methods struggle to address effectively. This work investigates the impact of 16 types of attacks on EVCS, such as denial-of-service (DoS), reconnaissance, cryptojacking, and backdoor attacks. To address these threats, we propose an innovative model designed to identify diverse cyber threats targeting EVCS. The proposed Temporal Convolutional Network (TCN)-based Intrusion Detection System (IDS) architecture integrates four key innovations: multi-receptive fields, a gating mechanism, iterative dilation, and a self-attention mechanism combined with a Squeeze-and-Excitation (SE) block to recalibrate feature responses by explicitly modeling interactions between different channels. The proposed model effectively processes multiple temporal scales, regulates the flow of information, adapts to varying time steps, and focuses on essential components of time-series data. Experimental evaluations demonstrate that the proposed model outperforms state-of-the-art methods in terms of accuracy and detection rates across all 16 attack types in the CICEVSE2024 dataset, which comprises extensive attack vectors and variants associated with the OCPP. The proposed approach achieves higher accuracy compared to other TCN variants and exhibits high resilience against complex attacks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1033-1050"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10959074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Multiple Small Biased GPS Spoofing Attacks on Autonomous Vehicles Using Time Series Analysis","authors":"Ahmad Mohammadi;Reza Ahmari;Vahid Hemmati;Frederick Owusu-Ambrose;Mahmoud Nabil Mahmoud;Parham Kebria;Abdollah Homaifar","doi":"10.1109/OJVT.2025.3559461","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3559461","url":null,"abstract":"This research introduces an algorithm to identify GPS spoofing attacks in Autonomous Vehicles (AV). It uses data from onboard sensors such as speedometers and gyroscopes, which are integrated and analyzed using a Neural Network (NN). This network predicts the vehicle's future displacement and compares these predictions with GPS data to identify potential spoofing attacks such as turn-by-turn, stop, and overshoot incidents. Additionally, the same sensor data is evaluated using an analytical model based on the vehicle's dynamic equations to assess its position and speed against GPS information. To facilitate real-time detection, a threshold is pre-established from clean datasets, which determines the largest expected differences between sensor readings and GPS data. This threshold is then used for ongoing real-time assessments to detect spoofing activities. Moreover, the algorithm can detect multiple small biased attacks, incremental attacks that may not initially exceed the established threshold but eventually result in significant discrepancies in GPS and Inertial Measurement Unit (IMU) reported displacement and speeds. This detection is facilitated through time series analysis at 25 and 50 s intervals to build a profile of data errors and distribution to predict the probability of such attacks. To evaluate the algorithm's effectiveness, five different test datasets depicting four types of spoofing scenarios—turn-by-turn, overshoot, stop, and multiple small biased attacks—were created using data from the publicly accessible Honda Research Institute Driving Dataset (HDD). The analysis shows that the model accurately detects these types of attacks with average accuracies of 98.62<inline-formula><tex-math>$pm$</tex-math></inline-formula>1%, 99.96<inline-formula><tex-math>$pm$</tex-math></inline-formula>0.1%, 99.88<inline-formula><tex-math>$pm$</tex-math></inline-formula>0.1%, and 95.92<inline-formula><tex-math>$pm$</tex-math></inline-formula>1.7% respectively.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1152-1163"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10959070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-Blind Channel Estimation and Achievable Rate Analysis for Uplink RIS-Enhanced Multi-User Networks","authors":"Samar I. Farghaly;Mohamed I. Ismail;Mostafa M. Fouda;Ahmed S. Alwakeel","doi":"10.1109/OJVT.2025.3557314","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3557314","url":null,"abstract":"Future wireless networks could benefit from the energy-efficient, low-latency, and scalable deployments that Reconfigurable Intelligent Surfaces (RISs) offer. However, the creation of an effective low overhead channel estimate technique is a major obstacle in RIS-assisted systems, especially given the high number of RIS components and intrinsic hardware constraints. This research examines the uplink of a RIS-empowered multi-user MIMO communication system and presents a novel semi-blind channel estimate approach. Unlike current approaches, which rely on pilot-based channel estimation, our methodology uses data to estimate channels, considerably enhancing the achievable rate. We provide a closed-form deterministic expression for the uplink achievable rate in actual settings where the channel state information (CSI) must be estimated rather than assumed perfect. The results of the simulations show that the formula obtained is accurate, with a close alignment between the deterministic and actual achievable rates (generally between 2 5% deviations). The proposed approach outperforms traditional approaches, resulting in rate increases of up to 35–40%, especially in instances with more RIS elements. These findings illustrate RIS technology's tremendous potential to improve system capacity and coverage, providing useful insights for optimizing RIS adoption in future wireless networks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1108-1139"},"PeriodicalIF":5.3,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10947543","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DelAwareCol: Delay Aware Collaborative Perception","authors":"Ahmed N. Ahmed;Siegfried Mercelis;Ali Anwar","doi":"10.1109/OJVT.2025.3556381","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3556381","url":null,"abstract":"Multi-agent collaborative perception has gained significant attention due to its ability to overcome the challenges stemming from the limited line-of-sight visibility of individual agents that raised safety concerns for autonomous navigation. Despite notable progress in collaborative perception, several persistent challenges hinder optimal performance, such as the size of data being shared, communication delays, computationally expensive collaboration mechanisms, and spatial misalignment. To address these challenges, we propose DelAwareCol, a versatile collaborative perception framework that tackles the transmission delay between connected agents in real-life autonomous driving. Our framework introduces three key modules designed to balance perception performance with communication bandwidth and delay. Firstly, an intra-agent information aggregation module captures valuable semantic cues within the temporal context to enhance the local representation of each ego agent. Secondly, an inter-agent information aggregation module manages inter-agent interactions and spatial relationships, addressing common vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) issues, such as spatial misalignment, asynchronous information sharing, and pose errors. Thirdly, an adaptive fusion mechanism integrates multi-source representations based on dynamic contributions from different agents. The proposed framework is validated on large-scale simulated and real-life collaborative perception datasets OPV2V, V2XSet, and V2VReal. Our experimental results demonstrate that DelAwareCol achieved state-of-the-art performance in collaborative object detection, maintaining robust performance in the presence of high latency and localization error.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1164-1177"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10946103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Space-Air-Ground Integrated Networks: Their Channel Model and Performance Analysis","authors":"Chao Zhang;Qingchao Li;Chao Xu;Lie-Liang Yang;Lajos Hanzo","doi":"10.1109/OJVT.2025.3575360","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3575360","url":null,"abstract":"Given their extensive geographic coverage, low Earth orbit (LEO) satellites are envisioned to find their way into next-generation (6G) wireless communications. This paper explores space-air-ground integrated networks (SAGINs) leveraging LEOs to support terrestrial and non-terrestrial users. We first propose a practical satellite-ground channel model that incorporates five key aspects: 1) the small-scale fading characterized by the Shadowed-Rician distribution in terms of the Rician factor <inline-formula><tex-math>$K$</tex-math></inline-formula>, 2) the path loss effect of bending rays due to atmospheric refraction, 3) the molecular absorption modelled by the Beer-Lambert law, 4) the Doppler effects including the Earth's rotation, and 5) the impact of weather conditions according to the International Telecommunication Union Recommendations (ITU-R). Harnessing the proposed model, we analyze the long-term performance of the SAGIN considered. Explicitly, the closed-form expressions of both the outage probability and of the ergodic rates are derived. Additionally, the upper bounds of bit-error rates and of the Goodput are investigated. The numerical results yield the following insights: 1) The shadowing effect and the ratio between the line-of-sight and scattering components can be conveniently modelled by the factors of <inline-formula><tex-math>$K$</tex-math></inline-formula> and <inline-formula><tex-math>$m$</tex-math></inline-formula> in the proposed Shadowed-Rician small-scale fading model. 2) The atmospheric refraction has a modest effect on the path loss. 3) When calculating the transmission distance of waves, Earth's curvature and its geometric relationship with the satellites must be considered, particularly at small elevation angles. 3) High-frequency carriers suffer from substantial path loss, and 4) the Goodput metric is eminently suitable for characterizing the performance of different coding as well as modulation methods and of the estimation error of the Doppler effects.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1501-1523"},"PeriodicalIF":5.3,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11018358","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous Hairpin Winding Technology for Electric Machines Enabling Net Zero Transportation: A Comprehensive Review","authors":"Hailin Huang;Tianjie Zou;Mauro Di Nardo;Amedeo Vannini;Anh Thanh Huynh;Michele Degano;David Gerada;Tao Yang;Chris Gerada","doi":"10.1109/OJVT.2025.3575187","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3575187","url":null,"abstract":"Featured by low power losses and strong heat dissipation capability, hairpin winding has been widely accepted as a key enabler of boosting performance for traction/propulsion electrical machines in automotive and aerospace sectors. Continuous hairpin winding (CHW), distinguished by its further improvement brought to machines’ key performance indicators, being power density, efficiency, and reliability, is emerging as a more promising winding solution. This paper will provide a critical technology review on CHW, with focus on highlighting its different features compared with those of other typical winding types, manufacturing/assembly process, layout design rules, as well as current and future development trends. Based on illustration of the unique winding process, the so-called “radial shift” feature that inherently exists in CHW will be introduced. The key elements in winding layout development, including transposition, terminal and jumper connections, parallel branch number, will be summarised for CHW. Moreover, new technology bricks and research ideas that strive to tackle manufacturing challenges, enhance design flexibility, as well as improve overall performance have been highlighted. Finally, the paper concludes by proposing future research directions, with the vision of increasing its Technology Readiness Level (TRL) for future net-zero transportation.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1481-1500"},"PeriodicalIF":5.3,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11018389","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interference Minimization in Beyond-Diagonal RIS-Assisted MIMO Interference Channels","authors":"Ignacio Santamaria;Mohammad Soleymani;Eduard Jorswieck;Jesús Gutiérrez","doi":"10.1109/OJVT.2025.3555425","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3555425","url":null,"abstract":"This paper proposes a two-stage approach for passive and active beamforming in multiple-input multiple-output (MIMO) interference channels (ICs) assisted by a beyond-diagonal reconfigurable intelligent surface (BD-RIS). In the first stage, the passive BD-RIS is designed to minimize the aggregate interference power at all receivers, a cost function called interference leakage (IL). To this end, we propose an optimization algorithm in the manifold of unitary matrices and a suboptimal but computationally efficient solution. In the second stage, users' active precoders are designed under different criteria such as minimizing the IL (min-IL), maximizing the signal-to-interference-plus-noise ratio (max-SINR), or maximizing the sum rate (max-SR). The residual interference not cancelled by the BD-RIS is treated as noise by the precoders. Our simulation results show that the max-SR precoders provide more than <inline-formula><tex-math>$20%$</tex-math></inline-formula> sum rate improvement compared to other designs, especially when the BD-RIS has a moderate number of elements and users transmit with high power, in which case the residual interference is still significant.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1005-1017"},"PeriodicalIF":5.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10943135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}