Novel Roadside Unit Positioning Framework in the Context of the Vehicle-to-Infrastructure Communication System Based on AHP — Entropy for Weighting and Borda — VIKOR for Uniform Ranking

Abstract

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[Formula: see text]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[Formula: see text]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.