Al Asmari Abdullah Faiz, Alqubaysi Tariq, Alanazi Fayez, Almutairi Ahmed, Armghan Ammar
Civil Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia.
Department of Civil Engineering, College of Engineering, Northern Border University, Arar, Saudi Arabia.
PLoS One. 2025 Mar 17;20(3):e0318997. doi: 10.1371/journal.pone.0318997. eCollection 2025.
Smart cities use Intelligent Transportation Systems (ITS) to manage traffic by continuously communicating with roadside infrastructure and nearby vehicles. Paused handoff interrupts grounded congestion, signal supervision, and path-shifting knowledge. Paused handoffs occur when cars wait to interact owing to volatile neighbours or heavily crowded roadside units. In congested metropolitan areas, ITS vehicle communication interruptions are a significant issue. This research addresses this issue. Hence, the research introduces the Cooperative Longevity of Interaction Model (CLoIM) to enhance communication reliability by minimizing the impact of paused handoff. The model employs a hybrid trained herd optimization algorithm to improve the longevity for interaction between vehicles and roadside units, minimizing handoff interruptions. The approach dynamically adjusts search strategies to prioritize high longevity interactions, improving communication stability. Results show that CLoIM increases longevity by 10.81% and reduces the paused handoff lag by 9.17%, effectively addressing the challenges of vehicle density and mobility in ITS scenarios.
智慧城市利用智能交通系统（ITS），通过与路边基础设施和附近车辆持续通信来管理交通。暂停切换会中断地面拥堵、信号监控和路径切换知识。当车辆由于不稳定的邻域或路边单元严重拥挤而等待交互时，就会发生暂停切换。在拥堵的大都市地区，ITS车辆通信中断是一个重大问题。本研究解决了这一问题。因此，该研究引入了交互合作寿命模型（CLoIM），通过最小化暂停切换的影响来提高通信可靠性。该模型采用混合训练的群体优化算法来提高车辆与路边单元之间交互的寿命，最大限度地减少切换中断。该方法动态调整搜索策略，优先考虑高寿命交互，提高通信稳定性。结果表明，CLoIM将寿命提高了10.81%，并将暂停切换延迟降低了9.17%，有效应对了ITS场景中车辆密度和移动性的挑战。
