Revolutionising Transportation with Artificial Intelligence: Exploring Its Diverse Applications

Due to AI systems incredible speed, many industries and businesses, like that of transportation, are becoming more effective. The advancements made possible by AI includes very complex computer methods that approximate ways the brain of an individual works ^[1]. Artificial intelligence is being applied in the transportation industry to handle challenges including the increase in traffic for passengers, emissions of carbon dioxide, safety difficulties, and damaging the environment. Due to the wealth of resources available in the contemporary digital age, it is more probable to tackle these issues successfully and productively. In the rail sector, artificial intelligence approaches such the Pollen Pre-processor, Propose Fuzzy Model, and Enquiry Analyser are being used. For AI to be used effectively, one must have a full understanding of both the relationships between AI and existing information and the characteristics and components of the mass transportation system ^[2]. It is also essential that mobility companies acquire the skills to use these solutions to immediately alleviate congestion, boost consumer travel time dependability, and further enhance the cost and efficiency of their priceless assets. This article provides an overall summary of the AI approaches used across the globe to solve traffic issues, particularly those related to road traffic, reduce accidents, public transit. The overviews conclusion discusses the difficulties and restrictions faced by Application domains in the transportation sector.