Geofenced Predictive Safety for Autonomous Logistics Vehicles: MATLAB Simulation and Arduino Hardware-in-the-Loop Validation in High-Risk Urban Zones

The dynamic advancement of intelligent transportation systems holds the promise of a better future with higher levels of road safety and efficiency. Nevertheless, the interaction between intelligent logistics vehicles and other vulnerable road users in high-risk areas remains a major challenge. This project brings the promise of a better future concerning road safety to life through the design of an intelligent system for “geofencing.” Geofencing describes an intelligent system that uses intelligent boundaries to improve road safety. It involves establishing boundaries in areas of greater road-safety concern. Often, such boundaries intended to alert drivers of impending danger. However, in the project's design, the predictive intelligent system ensures that, once intelligent transportation systems detect an intelligent boundary layer, the vehicle slows down as it drives through it. The predictive intelligent system was developed using simulations in MATLAB, integrated with an Arduino hardware-in-the-loop. This research postulates that a layer of automated protection woven into the transportation network does not constrain mobility but provides additional reliability for autonomous logistics, especially in protecting the most vulnerable sectors of the population.