The positioning of roadside units (RSUs) in a vehicle-to-infrastructure (V2I) communication system may have an impact on network performance. Optimal RSU positioning is required to reduce cost and maintain the quality of service. However, RSU positioning is considered a difficult task because numerous criteria, such as the cost of RSUs, the intersection area and communication strength, affect the positioning process and must be considered. Furthermore, the conflict and trade-off amongst these criteria and the significance of each criterion are reflected on the RSU positioning process. Thus, this work proposes a new RSU positioning framework based on multicriteria decision-making (MCDM) in the context of the V2I communication system. Three stages are completed for this purpose. First, a real-time V2I hardware is developed to collect data. The developed hardware consists of multiple mobile nodes (i.e., cars with sending–receiving hardware devices) and physical RSUs. The RSUs and the devices in the cars are connected via the nRF24L01$+$PA/LNA transceiver module with Arduino Uno. Second, seven testing scenarios are identified toward acquiring the required data upon the connection of the V2I devices. Moreover, three evaluation attributes (i.e., number of packet losses [PKL], cost and ratio of intersection area [RIA]) are used to evaluate each scenario. A decision matrix is constructed on the basis of the crossover between ‘RSU positioning scenarios’ and ‘multi-evaluation attributes (i.e., PKL, cost and RIA)’. Third, the RSU positioning scenarios are ranked using MCDM techniques, such as the integrated analytic hierarchy process (AHP), entropy and group Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Furthermore, the Borda voting approach is used to aggregate multiple individual rankings into a uniform and final rank. Results indicate the following: (1) integrating AHP, entropy and VIKOR is effective for solving RSU positioning problems; (2) the VIKOR ranking results for individuals vary; (3) the rank of scenarios obtained from the group-VIKOR-based Borda voting context shows that the second scenario, which consists of four RSUs distributed along the street with a maximum distance of 200$$m between them and 2-m high antennas, is the best in terms of optimally placing the RSUs; and (4) significant differences are observed amongst the scores of the groups, indicating that the ranking results are valid.

车对基础设施 (V2I) 通信系统中路边单元 (RSU) 的定位可能会对网络性能产生影响。需要优化 RSU 定位以降低成本并保持服务质量。然而，RSU 定位被认为是一项艰巨的任务，因为许多标准，例如 RSU 的成本、交叉区域和通信强度，都会影响定位过程并且必须加以考虑。此外，这些标准之间的冲突和权衡以及每个标准的重要性都反映在RSU定位过程中。因此，这项工作在 V2I 通信系统的背景下提出了一种基于多准则决策 (MCDM) 的新 RSU 定位框架。为此目的完成了三个阶段。首先，开发了实时 V2I 硬件来收集数据。开发的硬件由多个移动节点（即带有发送-接收硬件设备的汽车）和物理 RS​​U 组成。RSU 和汽车中的设备通过 nRF24L01 连接$+$带有 Arduino Uno 的 PA/LNA 收发器模块。其次，确定了七个测试场景，以在连接 V2I 设备时获取所需数据。此外，三个评估属性（即丢包数[PKL]、成本和交叉区域比率[RIA]）用于评估每个场景。基于“RSU 定位场景”和“多评估属性（即 PKL、成本和 RIA）”之间的交叉构建决策矩阵。第三，使用 MCDM 技术对 RSU 定位场景进行排名，例如集成层次分析法 (AHP)、熵和组 Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR)。此外，Borda 投票方法用于将多个个人排名聚合成一个统一的最终排名。结果表明：(1) 将层次分析法、熵和VIKOR相结合，有效解决RSU定位问题；（2）个人的VIKOR排名结果不一；(3) 从基于 group-VIKOR 的 Borda 投票上下文中获得的场景排名表明，第二个场景由沿街道分布的四个 RSU 组成，最大距离为 200$$它们之间的 m 和 2 米高的天线，在最佳放置 RSU 方面是最好的；(4) 各组得分存在显着差异，说明排名结果有效。