Road Traffic Gesture Autonomous Integrity Monitoring Using Fuzzy Logic

Area of Science:

• Intelligent Transportation Systems
• Autonomous Driving Technology
• Fuzzy Logic Applications

Background:

• Unsignalized intersections pose challenges for autonomous vehicles (AVs) due to reliance on human gestural communication.
• Existing communication methods are incompatible with AVs, creating safety and efficiency concerns.
• A need exists for a communication system that bridges AVs and human drivers at intersections.

Purpose of the Study:

• To develop and evaluate a novel in-vehicle traffic light system for AV-human driver communication.
• To ensure backward compatibility with traditional vehicles without internet or cloud dependency.
• To improve traffic flow and safety at four-legged unsignalized intersections.

Main Methods:

• Implementation of a fuzzy logic-based system on a self-organizing network of eight ESP32 microcontrollers.
• Integration of GPS sensors and light-emitting diodes (LEDs) for vehicle positioning and signaling.
• Utilization of the ESPNow broadcast feature for direct vehicle-to-vehicle communication, eliminating the need for internet services.

Main Results:

• Simulations demonstrated successful communication between AVs and human drivers at intersections.
• The system achieved precise position classification and lane dispersion under 30 seconds.
• The developed system proved to be a cost-effective solution for enhancing intersection safety.

Conclusions:

• The fuzzy logic-based in-vehicle traffic light system effectively facilitates communication between autonomous and traditional vehicles.
• The system's design ensures backward compatibility and operational independence from cloud platforms.
• This technology offers a promising, low-cost solution for improving traffic management and safety at complex intersections.