IEEE Open Journal of Vehicular Technology最新文献

{"title":"Autonomous Vehicle Security: Hybrid Threat Modeling Approach","authors":"Amal Yousseef;Yu-Zheng Lin;Shalaka Satam;Banafsheh Saber Latibari;Jesus Pacheco;Soheil Salehi;Salim Hariri;Pratik Satam","doi":"10.1109/OJVT.2025.3580538","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3580538","url":null,"abstract":"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.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1774-1795"},"PeriodicalIF":5.3,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641055","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":"RIS-Based DOA Estimation for Communication-Assisted Sensing Systems Under Hardware Impairments","authors":"Xue Zhang;Ngoc Phuc Le;Mohamed-Slim Alouini","doi":"10.1109/OJVT.2025.3580041","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3580041","url":null,"abstract":"Reconfigurable intelligent surface (RIS)-based localization has received significant attention in wireless communication systems due to its potential for enabling non-line-of-sight (NLoS) wireless sensing. However, hardware impairments (HWIs) in non-ideal hardware adversely affect the localization performance. To address the issue, this work studies a RIS-aided passive sensing system with the presence of HWIs, where communications signals are used to sense targets. We propose a method to address a DOA estimation problem in three-dimensional (3D) space. Specifically, a low-rank matrix is first recovered by solving an atomic norm minimization (ANM) problem, which is not affected by interference signal and additive noise. Subsequently, a block Hankel matrix is constructed using the correlation information of the low-rank matrix. The elevation and azimuth angles between targets and RIS are then estimated by applying the modified matrix pencil (MMP) method on the block Hankel matrix. We also derive the Cramér-Rao Bound (CRB) with closed-form expressions for DOA estimation based on the proposed system model. The proposed algorithm can sense multiple targets and achieve parameter automatic pairing. Numerical results verify the superiority of the proposed algorithm over the traditional schemes.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1736-1748"},"PeriodicalIF":5.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11037246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597716","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":"Codebook Design for Parallel Dynamic Subarrays in Millimeter Wave Massive MIMO Systems","authors":"Qi Li;Fu-Chun Zheng;Ke Xu;Lianming Li","doi":"10.1109/OJVT.2025.3579690","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3579690","url":null,"abstract":"This paper investigates the codebook design for the novel parallel dynamic subarrays for millimeter-wave (mmWave) massive MIMO systems. To generate high-resolution patterns, we design a novel parallel dynamic subarray structure where each radio frequency (RF) chain is dynamically connected to a subarray consisting of an antenna subset from two parallel arrays. Given the high grating lobes, we further design a PS selection strategy and codeword to obtain a high-resolution pattern with low grating lobes. In particular, an exhaustive algorithm is first proposed to get the optimum subarray configuration strategy. The combined high-low resolution phase shifter (PS) architecture is then utilized to overcome the hardware limitation of constant amplitude. Finally, the cuckoo search algorithm is employed to search the phase distribution and obtain the final codeword. Simulation results demonstrate that the proposed scheme can generate high-resolution patterns with low grating lobes, thereby achieving improved system spectral efficiency (SE).","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1710-1720"},"PeriodicalIF":5.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11036689","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536383","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":"Towards Robust Autonomous Driving: Out-of-Distribution Object Detection in Bird's Eye View Space","authors":"Muhammad Asad;Ihsan Ullah;Ganesh Sistu;Michael G. Madden","doi":"10.1109/OJVT.2025.3579341","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3579341","url":null,"abstract":"In autonomous driving, understanding the surroundings is crucial for safety. Since most object detection systems are designed to identify known objects, they may miss unknown or novel objects, which can be dangerous. This study addresses Out-Of-Distribution (OOD) detection for vehicle-like unknown objects within the Bird's Eye View (BeV) space, a top-down representation of the environment that provides a comprehensive spatial layout crucial for scene understanding. Enhancing the model's adaptability to unfamiliar objects, we present two novel methods for detecting unknown objects in BeV space. Specifically, we introduce random patches and OOD objects in the environment to help the model identify both known objects, such as vehicles, and OOD objects. We also introduce a new dataset, NuScenesOOD, derived from the NuScenes dataset, which augments vehicles with patterns and shapes to challenge the model. Additionally, we address challenges such as patch size inconsistency and occlusion from moving frames in BeV space. Our method targets vehicle-shaped anomalies in the planar driving space, maintaining high accuracy for known and enhancing detection of unknown objects. This research contributes to making future autonomous vehicles safer by improving their ability to detect diverse vehicle like OOD objects in their environment.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1673-1685"},"PeriodicalIF":5.3,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11031213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519448","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":"Investigating Life Cycle Cost, Environmental and Social Impacts of a Lithium–Ion Battery Pack","authors":"Antonella Accardo;Gaia Gentilucci;Luca Pontone;Ezio Spessa","doi":"10.1109/OJVT.2025.3579221","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3579221","url":null,"abstract":"This study evaluates the environmental, economic, and social impacts of the life cycle of a battery pack for automotive applications. The analysis employs Life Cycle Assessment (LCA) for environmental assessment, Life Cycle Costing (LCC) for economic assessment, and Social Life Cycle Assessment (S-LCA) for social impact analysis. Key locations of non-European raw material extraction and refining are considered for the supply chain. Instead, European countries are considered the final destination for battery pack manufacturing and assembly, use, and End-of-Life (EoL). For the use and EoL phases, three scenarios are analyzed. The LCA results indicate that greenhouse gas emissions vary from 77.2 kg CO<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> -eq/kWh to 80.7 kg CO<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>-eq/kWh across the evaluated scenarios. Similarly, the economic assessment estimates LCCs between 77.7 EUR/kWh and 79.4 EUR/kWh, depending on the scenario. The S-LCA results highlight significant risks related to fair pay across numerous countries during the raw material extraction phase, particularly for cobalt (Democratic Republic of the Congo), manganese (South Africa), nickel (Australia), lithium (Australia), and graphite (China). In addition, the score for health and safety concerns presents high risks associated with cobalt, manganese, and nickel mining. In contrast, no significant critical social impacts are found for the use and EoL phases.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1698-1709"},"PeriodicalIF":5.3,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11031181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536382","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":"Estimation of the Internal Temperature of High-Capacity Li-Ion Cells Using Embedded Impedancemetry","authors":"Charles Bechara;Guy Friedrich;Christophe Forgez;Samuel Cregut","doi":"10.1109/OJVT.2025.3579059","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3579059","url":null,"abstract":"The internal temperature of electrochemical accumulators is a crucial parameter that significantly impacts their aging and safety. In particular, the phenomenon of thermal runaway must be detected early due to its rapid progression and potentially catastrophic consequences. However, measuring the temperature of each cell within a battery pack is costly and typically only provides access to the external temperature of the elements. Moreover, as cell size increases, their thermal capacity also rises, leading to a significant time lag between the internal temperature and the surface temperature. Electrochemical Impedance Spectroscopy is a precise method for assessing electrochemical parameters and phenomena, which are closely correlated with the internal temperature of batteries; therefore, temperature estimation can be achieved using impedance measurements. This article presents an innovative, low-cost approach using an embedded version of the impedance spectroscopy technique to estimate the internal temperature of high-capacity 175 Ah Li-ion cells, which exhibit very low impedances (less than 1 m<inline-formula><tex-math>$Omega$</tex-math></inline-formula> on average). Experimental results demonstrate that embedded impedancemetry enables internal temperature estimation of individual cells in a battery pack with an RMSE of 1.5 <inline-formula><tex-math>$^{circ }$</tex-math></inline-formula> C.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1686-1697"},"PeriodicalIF":5.3,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11031187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536312","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":"Comparison of Reinforcement Learning Approaches for Automated Control Derivation in Design Space Exploration for Safety-Critical Automotive Applications","authors":"Patrick Hoffmann;Kirill Gorelik;Valentin Ivanov","doi":"10.1109/OJVT.2025.3578225","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3578225","url":null,"abstract":"This paper explores reinforcement learning for automated control derivation within design space exploration with focus on a functional safety concept for safety-critical automotive applications. A multi-task reinforcement learning framework is proposed to handle optimal control for various system topologies, component dimensioning, failures and scenarios. The timing analysis reveals that increasing the number of design variants significantly reduces per-topology training time, demonstrating the scalability of the proposed multi-task reinforcement learning approach for exploring large design spaces. This enables the derivation of optimal control across the entire design space, including both normal and failure conditions, while accounting for non linear plant dynamics with non-ideal actuator dynamics. The proposed methodology reduces manual engineering effort, supports derivation of fault tolerant control and offers a practical path toward automation in large-scale design space explorations.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1631-1649"},"PeriodicalIF":5.3,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11029148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502853","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":"Geographically Distributed Test Environment: Validation of Integrated Motion Control of Multi-Actuated Electric Vehicle","authors":"Viktar Beliautsou;Viktor Skrickij;Jesús Alfonso;Joris Giltay;Florian Büchner;Jose Angel Castellano;Barys Shyrokau;Valentin Ivanov","doi":"10.1109/OJVT.2025.3578224","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3578224","url":null,"abstract":"As an example of a geographically distributed test environment, an integrated motion control system for multi-actuated electric vehicles has been proposed and evaluated. This system unifies three active subsystems: drive-by-wire propulsion with independent in-wheel electric motors, electro-hydraulic brake actuators, and active suspension actuators. A distributed X-in-the-loop network architecture supports the approach, integrating a real-time validated vehicle model, dedicated test benches for each subsystem, and a driving simulator located in different geographical locations. This setup enables real-time testing and validation of the integrated control strategy. Validation results show improved ride comfort and safety.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1661-1672"},"PeriodicalIF":5.3,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11029149","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502854","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":"HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction","authors":"Junghee Kim;Wansik Choi;Changsun Ahn","doi":"10.1109/OJVT.2025.3577109","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3577109","url":null,"abstract":"This study presents the development and validation of a game theory-based controller for power distribution in hybrid electric vehicles, motivated by the limitations of conventional strategies that rigidly follow driver torque commands. Traditional control methods often assume strict compliance with driver input, which can constrain fuel efficiency. To address this, we propose a Stackelberg game-theoretic model that captures real-time driver-powertrain interaction, where the powertrain acts as a leader optimizing fuel consumption and the driver responds as a follower prioritizing ride comfort. This model introduces controlled deviations from the driver's torque commands to enhance energy efficiency without compromising drivability. The controller dynamically adapts to changing driving conditions without requiring prior route knowledge. Validation was conducted through simulations using a high-fidelity HEV model in MATLAB/Simulink for virtual drivers, and a CarSim-based driving simulator for human drivers. Experiments on urban (SC03) and high-speed (US06) cycles demonstrate that the proposed controller improves fuel economy by up to 5–10% compared to the Equivalent Consumption Minimization Strategy (ECMS), while maintaining high responsiveness as perceived by drivers. These findings highlight the practical potential of game-theoretic energy management in real-world HEV applications.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1568-1581"},"PeriodicalIF":5.3,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11025176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481931","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":"Explainable Federated Framework for Enhanced Security and Privacy in Connected Vehicles Against Advanced Persistent Threats","authors":"Sudhina Kumar G K;Krishna Prakasha K;Balachandra Muniyal;Muttukrishnan Rajarajan","doi":"10.1109/OJVT.2025.3576366","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3576366","url":null,"abstract":"The increasing adoption of autonomous and intelligent vehicles within ground transportation systems faces new security challenges. This shift from human-controlled operations opens up a broader attack surface for malicious players. As the interconnected Internet of Things (IoT) become ubiquitous in vehicles, they continuously generate and exchange a large amount of data. This tendency creates vulnerabilities that attackers can exploit using sophisticated techniques, such as Advanced Persistent Threats (APT). Detecting APTs in IoT-enabled vehicular environments is crucial. These APTs demand advanced detection mechanisms. The critical need for vehicular data privacy restricts traditional centralized Machine Learning (ML) approaches. Furthermore, the absence of publicly available APT datasets in the vehicular domain complicates model development and validation, creating a significant gap in cybersecurity capabilities for this evolving vehicular domain. This research proposes a novel Federated Deep Neural Network (FDNN) framework with a privacy-preserving technique to address these concerns. This study presents the key challenges in the APT detection phase and outlines the novel contributions to the body of knowledge. The research questions guiding the investigation are addressed and discussed. The features of the UNSW-NB15, Edge-IIoTset, and CSE-CIC-IDS2018 datasets are aligned with different stages of APT attacks. Using these datasets, the developed framework is analyzed and evaluated. For the mentioned datasets, the framework without privacy-preserving technique shows high APT detection accuracies of 97.32%, 96.81% and 98.06%, respectively. However, with the privacy-preserving technique, the framework shows 95.62%, 96.11% and 95.63% accuracies, respectively. All results with other evaluation metrics, such as Precision, False positive rate, F1 score etc., are tabulated. The developed framework is subjected to “Shapley Additive explanations (SHAP),” analysis to filter the considerably influential features in APT detection. This research establishes the efficacy of a novel framework for detecting APTs in distributed vehicular environments. The framework achieves superior performance by minimizing the number of data and reducing the number of features, which is demonstrated through rigorous experimentation on multiple benchmark datasets. The potential of the developed framework to detect the APTs in the cross-domain is discussed in future works.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1438-1463"},"PeriodicalIF":5.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11023215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314681","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}