The advent of self-driving cars and AI-enabled driving has brought a revolution in the way we travel and navigate in our daily lives. This study explores transport systems that put real-time context awareness and energy-efficiency first. The system uses Explainable AI to help drivers feel transparent and trusted, going beyond simple route optimization. The article reveals the system’s internal workings and discusses the main features of AI-enabled driving and navigation. It aims to dispel the mystery around Explainable AI by demonstrating how intricate algorithms are converted into understandable explanations for driver route suggestions. The system comes up with route recommendations and shows them with concise justifications for the AI’s logic. It is common practice for the driver or the commuter to follow the AI-driven directives of the navigation system blindly, without understanding the why and how of the directives. This gap in knowledge crops up a sense of distrust in the system and its effectiveness. It is this very hurdle where Explainable AI (XAI) comes in play and mitigates all the shortcomings. XAI takes effective steps toward making AI-driven decisions more informed and trustable for the user. This work focuses on the vital factors to be taken into account for explaining AI-driven decisions are discussed. A technique for evaluating the system’s cost-effectiveness is provided. It takes into account driver preferences and traffic in real time. It goes on to describe how this information is converted into understandable text or audio messages for drivers. This innovative transportation system, empowered by Explainable AI, empowers drivers to make informed choices while optimizing energy consumption and travel efficiency.