A Survey on Artificial Intelligence-Enabled Vehicular Ad-Hoc Networks (VANETs) for Smart Automotive Systems

Artificial Intelligence (AI) has turned into a new form of revolution in the automotive industry worldwide, pushing technological innovations, productivity, and safety through all stages of vehicle design, manufacturing, and autonomous performance.The importance of AI used to be underestimated, but it has now become one of the core technologies that help to facilitate automation, real-time decision-making, and predictive analytics.Using AI, machine learning, and computer vision, manufacturers are able to create vehicles with advanced driver assistance systems (ADAS), autonomous navigation, and smart user interfaces.Together with the Internet of Things (IoT), these innovations have formed highly interconnected ecosystems in which vehicles and other vehicles and infrastructure can interact via Vehicular Ad-hoc Networks (VANETs).This research paper explores how AI is changing the automotive industry, both in terms of technological adoption and in real-world uses.Descriptive research methodology was applied and primary data was collected using surveys of actual performance and virtual performance of the vehicle.The Chi-square test statistical validation showed that there are significant differences between the expected and observed results, which proves hypothesis that AI-based solutions can increase efficiency, safety, and reliability of modern vehicles.The study sheds light on the usefulness of AI in minimising human error, reducing accidents, and solving challenges related to aggressive driving and traffic congestion.The paper also discusses the uses of AI in driverless cars, artificial intelligence, predictive maintenance, and smart traffic light systems.Self-driving and adaptive vehicle control requires new technologies, such as deep-learning algorithms, sensor fusion, and better actuators.Meanwhile, AI-based virtual assistants like Amazon Alexa, Apple Car Play, and Google Android Auto are changing the way people interact with their vehicles by offering flawless voice-based assistants.These innovations also increase customer satisfaction by simplifying invehicle operations besides improving safety.In addition to driving applications, AI and data science are also used more in logistics, production, supply chain optimisation, and after-sale services in the automotive industry.Innovative optimisation and data-driven decision-making also allow manufacturers to automate procurement, enhance their marketing policies, and provide clients with personalised customer experiences.The transformative potential of these technologies has been well exhibited in carefully chosen use cases, and they are just in their infancy.Nonetheless, issues still persist, especially regarding safety, privacy, scalability, and regulatory conformance of implementing AI-based systems.These issues will be key in the mainstream implementation of autonomous vehicles and connected mobility solutions.