Traffic problems have increased in modern life due to a huge number of vehicles, big cities, and ignoring the traffic rules. Vehicular ad hoc network (VANET) has improved the traffic system in previous some and plays a vital role in the best traffic control system in big cities. But due to some limitations, it is not enough to control some problems in specific conditions. Now a day invention of new technologies of the Internet of Things (IoT) is used for collaboratively and efficiently performing tasks. This technology was also introduced in the transportation system which makes it an intelligent transportation system (ITS), this is called the Internet of vehicles (IOV). We will elaborate on traffic problems in the traditional system and elaborate on the benefits, enhancements, and reasons to better IOV by Systematic Literature Review (SLR). This technique will be implemented by targeting needed papers through many search phrases. A systematic literature review is used for 121 articles between 2014 and 2023. The IoV technologies and tools are required to create the IoV and resolve some traffic rules through SUMO (simulation of urban mobility) which is used for the design and simulation the road traffic. We have tried to contribute to the best model of the traffic control system. This paper will analysis two vehicular congestion control models in term of select the optimized and efficient model and elaborate on the reasons for efficiency by searching the solution SLR based questions. Due to some efficient features, we have suggested the IOV based on vehicular clouds. These efficient features make this model the best and most effective than the traditional model which is a great reason to enhance the network system.

翻译：随着车辆数量的激增、城市规模的扩大以及交通规则意识的淡薄，现代生活中的交通问题日益严峻。车载自组织网络（VANET）在一定程度上改善了交通系统，并在大城市的交通控制中发挥了关键作用。然而，由于某些局限性，它无法完全应对特定条件下的问题。近年来，新兴的物联网（IoT）技术被用于协作高效地执行任务。该技术也被引入交通运输系统，形成了智能交通系统（ITS），即车联网（IoV）。本文将阐述传统系统中的交通问题，并通过系统文献综述（SLR）阐明IoV的优势、改进之处及其推广理由。该方法将通过多个搜索短语锁定目标论文来实施。本研究对2014年至2023年间发表的121篇论文进行了系统文献综述。构建IoV需要相应的技术与工具，并通过SUMO（城市交通仿真）软件对部分交通规则进行设计与仿真。我们致力于提出最优的交通控制模型。本文将从选择高效优化模型的角度分析两种车辆拥塞控制模型，并通过基于SLR问题的解决方案阐述其高效性原因。基于部分高效特性，我们建议采用基于车辆云的IoV模型。这些特性使该模型比传统模型更优更有效，为网络系统的提升提供了重要依据。