Alsaleh Abdullah
Department of Computer Engineering, College of Computer and Information Sciences, Majmaah University, Majmaah, Saudi Arabia; Department of Information Engineering, Florence University, Florence, Italy.
Acta Psychol (Amst). 2025 May;255:104892. doi: 10.1016/j.actpsy.2025.104892. Epub 2025 Mar 12.
The rapid advancement of automotive technologies has spurred the development of innovative applications within intelligent transportation systems (ITS), aimed at enhancing safety, efficiency and sustainability. These applications, such as advanced driver assistance systems (ADAS), vehicle-to-everything (V2X) communication and autonomous driving, are transforming transportation by enabling adaptive cruise control, lane-keeping assistance, real-time traffic management and predictive maintenance. By leveraging cloud computing and vehicular networks, intelligent transportation solutions optimize traffic flow, improve emergency response systems, and forecast potential collisions, contributing to safer and more efficient roads. This study proposes a Vehicular Cloud-based Intelligent Transportation System (VCITS) model, integrating vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication through roadside units (RSUs) and cloudlets to provide real-time access to cloud resources. A novel search and management protocol, supported by a tailored algorithm, was developed to enhance resource allocation success rates for vehicles within a defined area of interest. The study also identifies critical security vulnerabilities in smart vehicle networks, emphasizing the need for robust solutions to protect data integrity and privacy. The simulation experiments evaluated the VCITS model under various traffic densities and resource request scenarios. Results demonstrated that the proposed model effectively maintained service availability rates exceeding 85 % even under high demand. Furthermore, the system exhibited scalability and stability, with minimal service loss and efficient handling of control messages. These findings highlight the potential of the VCITS model to advance smart traffic management while addressing computational efficiency and security challenges. Future research directions include integrating cybersecurity measures and leveraging emerging technologies like 5G and 6G to further enhance system performance and safety.
汽车技术的快速发展推动了智能交通系统(ITS)内创新应用的开发,旨在提高安全性、效率和可持续性。这些应用,如先进驾驶辅助系统(ADAS)、车与万物(V2X)通信和自动驾驶,通过实现自适应巡航控制、车道保持辅助、实时交通管理和预测性维护,正在改变交通运输。通过利用云计算和车辆网络,智能交通解决方案优化了交通流量,改进了应急响应系统,并预测潜在碰撞,有助于打造更安全、更高效的道路。本研究提出了一种基于车辆云的智能交通系统(VCITS)模型,通过路边单元(RSU)和云粒集成车对车(V2V)和车对基础设施(V2I)通信,以提供对云资源的实时访问。开发了一种由定制算法支持的新颖搜索和管理协议,以提高感兴趣的定义区域内车辆的资源分配成功率。该研究还识别了智能车辆网络中的关键安全漏洞,强调需要强大的解决方案来保护数据完整性和隐私。模拟实验在各种交通密度和资源请求场景下评估了VCITS模型。结果表明,即使在高需求情况下,所提出的模型也能有效保持超过85%的服务可用性率。此外,该系统表现出可扩展性和稳定性,服务损失最小,能够高效处理控制消息。这些发现凸显了VCITS模型在推进智能交通管理同时应对计算效率和安全挑战方面的潜力。未来的研究方向包括整合网络安全措施以及利用5G和6G等新兴技术进一步提高系统性能和安全性。