Revolutionizing Retail Logistics: Fine-Tuning 5G-Cyberphysical Vehicular Networks with AGSA-Driven Path Loss Models

Non-autonomous vehicles, like the MasterMover electric Tugs, find extensive application in specialised short-range communication settings such as UK's Tesco warehouses. Employing a resilient MasterMover setup, electromagnetic attenuation within the Cyberphysical vehicular infrastructure can be fine-tuned, thereby enhancing supply chain logistics for retail outlets. This study enhances an earlier conventional Agile Gravitational Search Algorithm (AGSA) with outdated path loss models. Through AGSA-driven path loss optimisation, subsequent regression analysis is employed to generate supervised labels for both observed and anticipated path loss behaviors. The findings are useful for new level 3-5 driverless cars operating at 5G/6G spectrum.