Mahmudul Hasan¹, Shuji Doman¹, A. S. M. Bakibillah², Md Abdus Samad Kamal^1,*, Kou Yamada¹

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-17, 2026, DOI:10.32604/cmc.2025.070222 - 10 November 2025

Abstract Traffic at urban intersections frequently encounters unexpected obstructions, resulting in congestion due to uncooperative and priority-based driving behavior. This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles (CAVs) at single-lane intersections, particularly in the context of left-hand side driving on roads. The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks. We consider that all approaching vehicles share relevant information through vehicular communications. The Intersection Coordination Unit (ICU) processes this information and communicates the optimal crossing or turning times to the vehicles. The primary objective of this… More >

Haotian Wu¹, Jiaming Pei², Jinhai Li^3,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069873 - 10 November 2025

Abstract With the increasing complexity of vehicular networks and the proliferation of connected vehicles, Federated Learning (FL) has emerged as a critical framework for decentralized model training while preserving data privacy. However, efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging. To address these issues, we propose Federated Learning with Client Selection and Adaptive Weighting (FedCW), a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks. FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts More >

Muflih Alhazmi¹, Waqar Ul Hassan², Saba Shaheen³, Mohammed M. A. Almazah⁴, Azmat Ullah Khan Niazi^3,*, Nafisa A. Albasheir⁵, Ameni Gargouri⁶, Naveed Iqbal⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1903-1940, 2025, DOI:10.32604/cmes.2025.072973 - 26 November 2025

Abstract This paper proposes a model-based control framework for vehicle platooning systems with second-order nonlinear dynamics operating over switching signed networks, time-varying delays, and deception attacks. The study includes two configurations: a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus (FNTBC) and Fixed-Time Bipartite Consensus (FXTBC), and a leader—follower structure ensuring structural balance and robustness against deceptive signals. In the leaderless model, a bipartite controller based on impulsive control theory, gauge transformation, and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays. The FNTBC achieves finite-time convergence depending on initial More >

Faareh Ahmed¹, Babar Mansoor², Muhammad Awais Javed³, Abdul Khader Jilani Saudagar^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3783-3804, 2025, DOI:10.32604/cmes.2025.069430 - 30 September 2025

Abstract Vehicular networks enable seamless connectivity for exchanging emergency and infotainment content. However, retrieving infotainment data from remote servers often introduces high delays, degrading the Quality of Service (QoS). To overcome this, caching frequently requested content at fog-enabled Road Side Units (RSUs) reduces communication latency. Yet, the limited caching capacity of RSUs makes it impractical to store all contents with varying sizes and popularity. This research proposes an efficient content caching algorithm that adapts to dynamic vehicular demands on highways to maximize request satisfaction. The scheme is evaluated against Intelligent Content Caching (ICC) and Random Caching More >

Tarak Nandy^1,*, Sananda Bhattacharyya²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 181-219, 2025, DOI:10.32604/cmc.2025.066306 - 29 August 2025

Abstract In the rapidly evolving landscape of intelligent transportation systems, the security and authenticity of vehicular communication have emerged as critical challenges. As vehicles become increasingly interconnected, the need for robust authentication mechanisms to safeguard against cyber threats and ensure trust in an autonomous ecosystem becomes essential. On the other hand, using intelligence in the authentication system is a significant attraction. While existing surveys broadly address vehicular security, a critical gap remains in the systematic exploration of Deep Learning (DL)-based authentication methods tailored to these communication paradigms. This survey fills that gap by offering a comprehensive… More >

Yiwei Zhang, Xin Cui^*, Qinghui Zhao

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2355-2373, 2025, DOI:10.32604/cmc.2025.065430 - 03 July 2025

Abstract The rapid advance of Connected-Automated Vehicles (CAVs) has led to the emergence of diverse delay-sensitive and energy-constrained vehicular applications. Given the high dynamics of vehicular networks, unmanned aerial vehicles-assisted mobile edge computing (UAV-MEC) has gained attention in providing computing resources to vehicles and optimizing system costs. We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption. We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm (DVCG-MWOA) to address this problem. A novel dynamic clustering algorithm is designed… More >

Jun Li^1,*, Yawei Dong¹, Liang Ni¹, Guopeng Feng¹, Fangfang Shan^1,2

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3537-3552, 2025, DOI:10.32604/cmc.2025.059325 - 16 April 2025

Abstract With the development of vehicle networks and the construction of roadside units, Vehicular Ad Hoc Networks (VANETs) are increasingly promoting cooperative computing patterns among vehicles. Vehicular edge computing (VEC) offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure, thereby reducing the computational burden on connected vehicles. However, this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation nodes. Existing vehicular edge computing platforms have not adequately considered the misbehavior of vehicles. We propose a practical task offloading algorithm based on reputation assessment to More >

Aishwarya Rajasekar^*, Vetriselvi Vetrian

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 225-254, 2025, DOI:10.32604/cmes.2025.062642 - 11 April 2025

Abstract The integration of technologies like artificial intelligence, 6G, and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle applications. However, these advancements also generate a surge in data processing requirements, necessitating the offloading of vehicular tasks to edge servers due to the limited computational capacity of vehicles. Despite recent advancements, the robustness and scalability of the existing approaches with respect to the number of vehicles and edge servers and their resources, as well as privacy, remain a concern. In this paper, a lightweight… More >

Kwang Chee Seng, Siti Fatimah Abdul Razak^*, Sumendra Yogarayan

Computer Systems Science and Engineering, Vol.49, pp. 239-258, 2025, DOI:10.32604/csse.2024.056582 - 10 January 2025

Abstract Vehicle overtaking poses significant risks and leads to injuries and losses on Malaysia’s roads. In most scenarios, insufficient and untimely information available to drivers for accessing road conditions and their surrounding environment is the primary factor that causes these incidents. To address these issues, a comprehensive system is required to provide real-time assistance to drivers. Building upon our previous research on a LoRa-based lane change decision-aid system, this study proposes an enhanced Vehicle Overtaking System (VOS). This system utilizes long-range (LoRa) communication for reliable real-time data exchange between vehicles (V2V) and the cloud (V2C). By More >

Mosab Manaseer¹, Maram Bani Younes^2,*

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1699-1721, 2024, DOI:10.32604/csse.2024.055128 - 22 November 2024

Abstract This work aims to examine the vulnerabilities and threats in the applications of intelligent transport systems, especially collision avoidance protocols. It focuses on achieving the availability of network communication among traveling vehicles. Finally, it aims to find a secure solution to prevent blackhole attacks on vehicular network communications. The proposed solution relies on authenticating vehicles by joining a blockchain network. This technology provides identification information and receives cryptography keys. Moreover, the ad hoc on-demand distance vector (AODV) protocol is used for route discovery and ensuring reliable node communication. The system activates an adaptive mode for monitoring More >