Wang Jingwen, Topilin Ivan, Feofilova Anastasia, Shao Mengru, Wang Yadong
Don School, International Education College, Shandong Jiaotong University, Jinan 250357, China.
Faculty of Road and Transportation, Don State Technical University, 1 Gagarin sq., Rostov-on-Don 344000, Russia.
Sensors (Basel). 2025 Mar 27;25(7):2132. doi: 10.3390/s25072132.
The advancement of intelligent road transport represents a promising direction in the evolution of transportation systems, aimed at improving road safety and reducing traffic accidents. The integration of artificial intelligence, sensors, and machine vision systems enables autonomous vehicles (AVs) to rapidly adapt to changes in the road environment, minimizing human error and significantly reducing collision risks. These technologies provide continuous and highly precise control, including adaptive acceleration, braking, and maneuvering, thereby enhancing overall road safety. Connected vehicles utilizing C-V2X (Cellular Vehicle-to-Everything) communication primarily feature real-time operation, safety, and stability. However, communication flaws, such as signal fading, time delays, packet loss, and malicious network attacks, can affect vehicle-to-vehicle interactions in cooperative intelligent transport systems (C-ITSs). This study explores how C-V2X technology, compared to traditional DSRC, improves communication latency and enhances vehicle communication efficiency. Using SUMO simulations, various traffic scenarios were modeled with different autonomous vehicle penetration rates and communication technologies, focusing on traffic conflict rates, travel time, and communication performance. The results demonstrated that C-V2X reduced latency by over 99% compared to DSRC, facilitating faster communication between vehicles and contributing to a 38% reduction in traffic conflicts at 60% AV penetration. Traffic flow and safety improved with increased AV penetration, particularly in congested conditions. While C-V2X offers substantial benefits, challenges such as data packet loss, communication delays, and security vulnerabilities must be addressed to fully realize its potential. Future advancements in 5G and subsequent wireless communication technologies are expected to further reduce latency and enhance the effectiveness of C-ITSs. This study underscores the potential of C-V2X to enhance collision avoidance, alleviate congestion, and improve traffic management, while also contributing to the development of more reliable and efficient transportation systems. The continued refinement of simulation models and collaboration among stakeholders will be crucial to addressing the challenges in CAV integration and realizing the full benefits of connected transportation systems in smart cities.
智能道路运输的发展是交通系统演进中一个很有前景的方向，旨在提高道路安全性并减少交通事故。人工智能、传感器和机器视觉系统的集成使自动驾驶车辆能够快速适应道路环境的变化，将人为错误降至最低，并显著降低碰撞风险。这些技术提供持续且高度精确的控制，包括自适应加速、制动和操纵，从而提高整体道路安全性。利用蜂窝车联网（C-V2X）通信的联网车辆主要具有实时运行、安全性和稳定性的特点。然而，诸如信号衰落、时延、数据包丢失和恶意网络攻击等通信缺陷，会影响协同智能交通系统（C-ITS）中的车对车交互。本研究探讨了与传统专用短程通信（DSRC）相比，C-V2X技术如何改善通信延迟并提高车辆通信效率。通过使用SUMO模拟，针对不同的自动驾驶车辆渗透率和通信技术对各种交通场景进行建模，重点关注交通冲突率、行程时间和通信性能。结果表明，与DSRC相比，C-V2X将延迟降低了99%以上，促进了车辆之间更快的通信，并在自动驾驶车辆渗透率达到60%时使交通冲突减少了38%。随着自动驾驶车辆渗透率的提高，交通流量和安全性得到改善，特别是在拥堵情况下。虽然C-V2X带来了诸多好处，但必须解决诸如数据包丢失、通信延迟和安全漏洞等挑战，以充分发挥其潜力。预计5G及后续无线通信技术的未来发展将进一步降低延迟并提高C-ITS的有效性。本研究强调了C-V2X在增强碰撞避免、缓解拥堵和改善交通管理方面的潜力，同时也为更可靠、高效的交通系统的发展做出了贡献。持续完善模拟模型以及利益相关者之间的合作对于应对自动驾驶车辆集成中的挑战并实现智能城市中联网交通系统的全部益处至关重要。
