Scalable Edge Computing and Energy-Aware Routing for Autonomous, Connected, and Electric Vehicles

This thesis proposes a unified framework to improve computational efficiency and energy-aware navigation in Intelligent Transportation Systems with Autonomous, Connected, and Electric vehicles. It introduces a Serverless Vehicular Edge Computing model for low-latency offloading of compute-intensive tasks and an advanced EV routing algorithm using real-time traffic, charging availability, and wait times. Together, these innovations reduce latency for safety-critical functions and enhance energy efficiency and travel reliability, supporting scalable and sustainable mobility solutions.