In the last few years, transportations has encountered several main changes, from fossil energy to electrical, and from basic mechanical technology to high electronic diagnostics and monitoring. This latter, by deploying a several number of sensors and actuators, had led the researchers to develop the autonomous vehicles. Firstly, the decision control system was based on programing algorithms, but rapidly they integrated the Artificial Intelligence (IA) that will help making transportation safer and more charge effective. It merges the latest AI technologies of machine learning and neural networks for real-time analysis of environmental details with an accurate view of the problem, adaptive speed control, and navigation. Under addition to improving the efficiency and safety of transportation, AI-driven techniques include statistical models that minimize accidents and maximize energy use, even under challenging conditions. Sensors like lidar-light dissection and ranging radar, and cameras create good situational realization even in difficult situations. Lastly, advancements in Internet of Things technologies and AI-based decision-making systems have significantly increased vehicle safety and decreased energy consumption in recent years. Significant technological obstacles in the design of autonomous vehicles are also highlighted in the study, such as the requirement for legislative frameworks, computing costs, and data security risks. The essay explains how AI-powered autonomous cars are able to take control over energy capacity, safety, and infrastructure investment. This paper presents a review of different autonomous vehicles strategies, which will allow to locate the advancement of other researchers in the field of artificial intelligence making decision systems and internet of things to promote vehicle’s safety and energy consumption reduction.