Vehicular Communications最新文献

{"title":"Geometric Optimisation of Unmanned Aerial Vehicle Trajectories in Uncertain Environments","authors":"J Akshya ,&nbsp;M Sundarrajan ,&nbsp;S. Amutha ,&nbsp;Rajesh Kumar Dhanaraj ,&nbsp;Adil O. Khadidos ,&nbsp;Alaa O. Khadidos ,&nbsp;Shitharth Selvarajan","doi":"10.1016/j.vehcom.2025.100938","DOIUrl":"10.1016/j.vehcom.2025.100938","url":null,"abstract":"<div><div>The problem of efficient trajectory optimisation for Unmanned Aerial Vehicles (UAVS) in dynamic and constrained environments is one where energy efficiency, spatial coverage, and path smoothness need to be balanced. The existing methods, namely RRT*, A*, and Dijkstra, are popular but generally heuristic and do not provide globally optimal solutions. They face significant limitations while dealing with complex geometries, dynamic obstacles, and multi-objective requirements. These challenges call for a mathematically sound framework that seamlessly integrates convex analysis and computational geometry to provide an optimal trajectory planning framework. This research work introduces a convex optimisation framework for UAV trajectory planning which unifies multiple objectives, like minimising energy consumption, maximising spatial coverage, and ensuring the smoothness of the path, into a single convex objective function. More importantly, it indicates that obstacle dynamics and uncertain environmental conditions are handled better by it, so it is relatively easier for safe and efficient navigation. Proven to converge faster and with higher precision than RRT*, A*, and Dijkstra, the approach proposed here enjoys intrinsic convex properties, which ensure global optimality. Qualitative measurements show the efficiency of the proposed framework. The result is energy efficiency of 90%, with 92% coverage, 98% constraint satisfaction, and 95% path smoothness, which is 15-25% better on all metrics than traditional approaches can offer. By bridging between theory in convex optimisation and practice for solving multi-objective problems in a dynamic setting, this study provides a more robust solution for UAV trajectory planning.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100938"},"PeriodicalIF":5.8,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rigid communication topologies: Impact on stability, safety, energy consumption, passenger comfort, and robustness of vehicular platoons","authors":"Amir Zakerimanesh ,&nbsp;Tony Zhijun Qiu ,&nbsp;Mahdi Tavakoli","doi":"10.1016/j.vehcom.2025.100936","DOIUrl":"10.1016/j.vehcom.2025.100936","url":null,"abstract":"<div><div>This paper investigates the impact of rigid communication topologies (RCTs) on the performance of vehicular platoons, aiming to identify beneficial features in RCTs that enhance vehicles behavior. Four performance metrics are introduced, focusing on safety, energy consumption, passenger comfort, and robustness of vehicular platoons. The safety metric is based on momentary distances between neighboring vehicles, their relative velocities, and relative accelerations. Thus, to have access to these relative values, the coupled dynamics between pairs of neighboring vehicles are formulated, considering initial conditions (position, velocity, acceleration), the velocity/acceleration trajectory of the leader vehicle, deployed RCT, and the parity/disparity between vehicles. By decoupling the dynamics using a mapping matrix structured on deployed RCT, the features of the vehicles, and control gains, precise formulations for distance errors, relative velocities, and relative accelerations between all neighboring vehicles, over the travel time, are obtained. Comparing performance metric results across RCTs highlights that downstream information transmission—from vehicles ahead, particularly the leader vehicle, to vehicles behind—significantly enhances platoon stability, safety, energy consumption, and passenger comfort metrics. Conversely, receiving state information from vehicles behind degrades metrics, compromising safety, increasing energy consumption, and reducing passenger comfort. These findings underscore that forward-looking, leader-centric communications between vehicles markedly enhance platoon efficiency and safety.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100936"},"PeriodicalIF":5.8,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An optimal transmit power allocation scheme using UAV position estimation in MmWave NTNs","authors":"Pawan Srivastava,&nbsp;M.P.R.S. Kiran","doi":"10.1016/j.vehcom.2025.100934","DOIUrl":"10.1016/j.vehcom.2025.100934","url":null,"abstract":"<div><div>Non-terrestrial networks (NTNs) typically consist of UAV swarms equipped with multiple sensors that generate massive data, requiring real-time communication to a gateway for further processing. Hence, millimeter-wave (mmWave) communication technologies operating above 24 GHz emerge as a suitable solution for enabling high-speed intra-UAV swarm communication. However, mmWave communication technologies use multiple antenna-based directional beamforming for improved coverage, which leads to higher power consumption and frequent beam training overhead, affecting swarm endurance. To address this, we propose a novel optimal transmit power allocation scheme that enhances swarm endurance and improves throughput by reducing beam training overhead. Firstly, the proposed scheme uses the Kalman filter (in this paper, but not limited to) at the transmitting UAV to estimate the real-time position of the receiving UAV. The estimated position is utilized to calculate path loss and select the optimal transmit power level needed to meet the required received signal power threshold at the receiving UAV. To reduce outages from errors in UAV position estimation, the proposed scheme also adjusts the transmit power level by incorporating an additional buffer distance around the estimated position, thereby enhancing reliability with a minimal increase in transmit power. The performance analysis shows that the proposed scheme achieves an average reliability of more than 99% and power savings of up to 49.4% while increasing the throughput under saturated traffic conditions, thus establishing its effectiveness in mobile UAV swarms. Also, the proposed scheme is compared with three popular mechanisms existing in the literature: 1) baseline approach where constant transmit power is utilized, 2) deep learning (long short-term memory, LSTM) based transmit power allocation, and 3) power allocation using <span><math><mi>α</mi><mo>−</mo><mi>β</mi><mo>−</mo><mi>γ</mi></math></span> filter for receiving UAV position estimation. The performance comparison shows that the proposed scheme offers superior performance in terms of power savings, reliability, throughput, and computational complexity.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100934"},"PeriodicalIF":5.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DAME-IoV: Dynamic Adaptive Multi-Edge authentication protocol with post-quantum security for Internet of Vehicles","authors":"Iftikhar Rasheed ,&nbsp;Hala Mostafa","doi":"10.1016/j.vehcom.2025.100933","DOIUrl":"10.1016/j.vehcom.2025.100933","url":null,"abstract":"<div><div>The Internet of Vehicles (IoV) faces increasing security challenges with the advent of quantum computing, which threatens traditional cryptographic protocols while demanding efficient authentication mechanisms for large-scale vehicle networks. This paper presents DAME-IoV, a Dynamic Adaptive Multi-Edge authentication protocol that provides post-quantum security while leveraging edge computing capabilities for enhanced performance. Our framework introduces three key innovations: (1) a lightweight post-quantum authentication scheme optimized for vehicular networks, featuring lattice-based cryptography with dynamic parameter adjustment; (2) an adaptive security mechanism that dynamically adjusts protection levels based on real-time threat assessment and resource availability; and (3) an efficient edge-assisted processing architecture that enables scalable authentication through intelligent caching and batch verification. We provide formal security proofs demonstrating the protocol's resistance to quantum attacks while maintaining conditional privacy preservation. Extensive experimental evaluation on a prototype implementation shows that DAME-IoV achieves 45% lower computational overhead, 35% reduced memory footprint, and 40% better scaling efficiency compared to existing solutions. Performance analysis under various network conditions demonstrates that our framework maintains authentication latency below 50 ms while supporting over 1000 concurrent vehicle requests. The proposed solution successfully addresses the critical challenges of post-quantum security, scalability, and efficiency in IoV environments, providing a practical foundation for securing next-generation vehicular networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100933"},"PeriodicalIF":5.8,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Capacity and outage analysis of SM-OTFS system with imperfect CSI in V2V communications","authors":"Zhiquan Bai ,&nbsp;Runlai Wang ,&nbsp;Yingchao Yang ,&nbsp;Huili Hu ,&nbsp;Jingxin Li ,&nbsp;Xiao Zhou ,&nbsp;Chengyou Wang ,&nbsp;Jian Dai","doi":"10.1016/j.vehcom.2025.100931","DOIUrl":"10.1016/j.vehcom.2025.100931","url":null,"abstract":"<div><div>With the continuous emergence of high-mobility communication scenarios, such as the Internet of Vehicles (IoV) and Vehicle to Vehicle (V2V) communications, more unique challenges have appeared in mobile communications, due to the severe Doppler frequency shift and fast time-varying channel caused by high mobility. Meanwhile, the moving speed, data volume, and quality of service are becoming more and more important in V2V communications. Providing efficient and reliable wireless communication services to high-mobility users has become a critical issue. Spatial modulation (SM) based orthogonal time frequency space (OTFS) (SM-OTFS) system can improve the reliability and effectiveness of V2V communications because of the excellent Doppler shift resistance of OTFS modulation and the low complexity of SM transmission. In this paper, considering the case that achieving perfect channel estimation is really challenging in actual situation, we derive and analyze the capacity and outage performance of the SM-OTFS system under the circumstance of ideal pulse and imperfect channel state information (CSI) based on the statistical probability and the delay-Doppler domain (DD) input-output relationship. Our theoretical analysis and derivation are approved by the numerical results. Moreover, we also demonstrate the effect of the number of resolvable multipaths, the error of channel estimation, and the different moving speeds on the performance of the SM-OTFS system in V2V communications.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100931"},"PeriodicalIF":5.8,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beamforming design and trajectory optimization for integrated sensing and communication supported by multiple UAVs based on DRL","authors":"Zekun Lu,&nbsp;Linbo Zhai,&nbsp;Wenjie Zhou,&nbsp;Kai Xue,&nbsp;Xingxia Gao","doi":"10.1016/j.vehcom.2025.100932","DOIUrl":"10.1016/j.vehcom.2025.100932","url":null,"abstract":"<div><div>With the rapid development of Unmanned aerial vehicle (UAV) technology and the high flexibility and maneuverability of UAV itself, UAV will play a very important role in the development of integrated sensing and communication (ISAC) in the future. In this paper, the communication and sensing system supported by multiple UAVs is studied. And we propose a new ISAC balance mode (BISAC). In this mode, the sensing time is set reasonably according to the number of potential targets (PTs) and sensing requirements while the UAV is communicating with ground equipment (GEs), so as to reduce the interaction between communication and sensing and improve the utilization of resources. We also introduce the Age of Information (AoI) to measure the freshness of GEs' data information in order to reduce the delay. Therefore, our goal is to minimize the Average AoI of GEs by jointly optimizing UAV trajectory, user association, target sensing selection and communication and sensing beamforming while maintaining communication quality and sensing requirements. In order to obtain long-term AoI performance and effectively solve non-convex problems with continuous and discrete variables, we propose a deep reinforcement learning (DRL) algorithm based on a combination of deep deterministic policy gradient (DDPG) and Dueling Double Deep Q networks (D3QN). Continuous and discrete variables in the system are processed by invoking a DDPG and D3QN. Specifically, we have improved DDPG's actor-critic structure by incorporating D3QN, which utilizes the actor portion of DDPG to search for optimal communication and sensing beams. At the same time, the critic part of DDPG is combined with D3QN to select the optimal flight direction of UAV. Simulation results show that the proposed DDPG-D3QN algorithm has better stability, faster convergence rate, and higher reward than existing DRL-based methods.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100932"},"PeriodicalIF":5.8,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the performance of a UAV-based Malaga-distributed FSO/FSO communication system with NOMA","authors":"Aanchal Gupta ,&nbsp;Divya Dhawan ,&nbsp;Neena Gupta ,&nbsp;Hemani Kaushal","doi":"10.1016/j.vehcom.2025.100930","DOIUrl":"10.1016/j.vehcom.2025.100930","url":null,"abstract":"<div><div>Non-Orthogonal Multiple Access (NOMA) is an efficient communication technique that can offer improved spectral efficiency, ultra-low latency and massive connectivity and its integration with Free Space Optical (FSO) communication can improve the network capacity to a great extent. In this manuscript, an Unmanned Aerial Vehicle (UAV) is employed as a relay in an FSO/FSO downlink network, comprising of two users, user 1, U1 and user 2, U2, using Amplify-and-Forward (AF) protocol. UAVs can prove to be assets in disaster-struck situations (during natural disasters such as earthquakes, floods, etc.), when all terrestrial communication is at halt. The performance of this system is determined in the presence of atmospheric attenuation, Malaga (<span><math><mi>M</mi></math></span>) turbulence fading, pointing errors and Angle-of-Arrival (AoA) fluctuations. Heterodyne detection (HD) technique is used for information detection at the users for providing improved sensitivity and Signal-to-Noise Ratio (SNR). The closed-form expressions for Outage Probability (OP), Ergodic Capacity and Bit Error Rate (BER) are derived in terms of Meijer-G function and OP is analyzed with respect to different weather conditions, turbulence levels, pointing error coefficients, NOMA coefficients and Field-of-View (FoV) angles. It is observed that at an SNR of 0 dB, the outage at U1 and U2 is 0.5489 and 0.7423, respectively. A comparison of OP is presented for the cases of HD and Intensity Modulation/Direct Detection (IM/DD) techniques and for NOMA and Orthogonal Multiple Access (OMA) technologies. Ergodic Capacity is analyzed for different turbulence strengths and pointing error values and it can be noticed that it is enhanced by reducing the turbulence strength and pointing error impairment. BER is observed for different modulation schemes and it is found to be <span><math><mn>7.7</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>3</mn></mrow></msup></math></span>, <span><math><mn>1.9</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span>, <span><math><mn>7.9</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span> and <span><math><mn>2.8</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span>, for QPSK, 8-PSK, 16-PSK and 16-QAM, respectively, at an SNR of 30 dB. In addition, BER is analyzed for clear, rainy and foggy weather along with different pointing errors and turbulence regimes. Monte-Carlo simulations are also carried out in order to validate the correctness of the obtained analytical results.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100930"},"PeriodicalIF":5.8,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A QoS-aware adaptive cross-layer cyber-attack detection algorithm for vehicular networks","authors":"Avneet Kaur ,&nbsp;Makhduma F. Saiyed ,&nbsp;Irfan Al-Anbagi ,&nbsp;M. Shamim Hossain","doi":"10.1016/j.vehcom.2025.100929","DOIUrl":"10.1016/j.vehcom.2025.100929","url":null,"abstract":"<div><div>Securing data transmission and detecting cyber-attacks in consumer Vehicular Ad hoc Networks (VANETs) pose significant challenges due to the highly dynamic topology of the network and frequent mobility of nodes. These characteristics enable attackers to exploit vulnerabilities and evade detection, making real-time attack detection complex while maintaining the Quality of Service (QoS). In this paper, we propose an Adaptive Cross-layer Cyber-attack Detection (ACCD) algorithm that dynamically detects and isolates malicious nodes while optimizing traffic routing based on application-specific requirements. The proposed algorithm uses a cross-layer traffic-aware approach to classify data flows into security-critical and delay-sensitive applications, ensuring optimal routing through the selection of Ant Colony Optimization (ACO) and Ad hoc On-Demand Multipath Distance Vector (AOMDV) protocols. The integration of pre-route authentication (PRA) enhances malicious node isolation, reducing the impact of selective forwarding and blocking attacks. Simulation results show that ACCD achieves lower end-to-end delay and higher Packet Delivery Ratio (PDR) while effectively balancing network security and performance.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100929"},"PeriodicalIF":5.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing security in vanets: Adaptive Bald Eagle Search Optimization based multi-agent deep Q neural network for Sybil attack detection","authors":"M. Ajin,&nbsp;R.S. Shaji","doi":"10.1016/j.vehcom.2025.100928","DOIUrl":"10.1016/j.vehcom.2025.100928","url":null,"abstract":"<div><div>Currently, the use of Vehicular Ad-Hoc Networks (VANETs) has gained significant attention in toll management systems and traffic control. VANETs facilitate effective communication by connecting Roadside Units (RSUs) and vehicles. VANETs can ease decision-making for drivers, meanwhile, they carry some problems with security since they often modify topology. In VANET, the Sybil attack is a specific attack, that might generate traffic congestion and affect transportation safety services. Different Mechanisms have been implemented to discover various attacks in VANET, yet VANET meets diverse attacks. Therefore, this research article developed an effective Sybil attack detection model namely Adaptive Bald Eagle Search Optimization (ABESO) based Multi-agent-Deep Q Neural network (MA-DQN). The principal objective of the ABESO based DQN is to enhance the security level of VANET by identifying the Sybil Attacks. In this, clustering and effective cluster head selection are performed to discover the Sybil attacks. In the suggested ABESO based DQN algorithm, robust clustering is carried out, in which vehicle nodes of VANET are clustered through the utilization of the BIRCH clustering technique. Our proposed ABESO based DQN algorithm augments the overall network efficiency by effective cluster head selection. Taylor-based Waterwheel Plant (TWP) is exploited in the cluster head selection and diminishes the overhead in the network. In the proposed model, the MDQN-based approach selects the features and ABESO based DQN delivers an optimal output, i.e., it discovers normal and Sybil attacks. Experimental results are carried out on the basis of the sybil attack detection dataset that holds multiple data regarding attacks. The detection results affirm that the efficiency of the proposed ABESO based DQN approach is superior and outperformed previous methods.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100928"},"PeriodicalIF":5.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging reputation for enhanced decision accuracy in vehicle-to-vehicle communications under limited infrastructure","authors":"Dimah Almani ,&nbsp;Tim Muller ,&nbsp;Steven Furnell","doi":"10.1016/j.vehcom.2025.100927","DOIUrl":"10.1016/j.vehcom.2025.100927","url":null,"abstract":"<div><div>Vehicle-to-Vehicle (V2V) networking enhances transportation safety and efficiency by enabling vehicles to share alerts. However, malicious vehicles may inject false messages, leading to disputes. While certificates help ensure security, Certificate Revocation List (CRLs) may be outdated in low-connectivity areas, making it hard to verify conflicting reports. Reputation systems, using a pre-signature scheme, can aid decision-making even in infrastructure-limited environments.</div><div>In this paper, we provide the mechanisms to use reputation in areas with low/no connectivity, whilst allowing for pseudonymous certificates to verify message authenticity without breaking privacy. The approach is integrated into the existing Security Credential Management System (SCMS), a framework for managing digital certificates for secure V2V communication.</div><div>Our simulations evaluate the security performance of our proposed mechanism, with offline available reputation, against plain SCMS certificate management that rely solely on CRL to block malicious vehicles. The results are achieved by integrating vehicular simulation tools like SUMO, OMNeT++, and Veins, to evaluate the V2V communications in each system under two conditions (Accident and No accident) ensuring a comprehensive system evaluation.</div><div>The proposed scheme improves accuracy in decision-making with conflicting information by 36% in accidents and 44.4% in No-Accident situations in a rural environment.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100927"},"PeriodicalIF":5.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}