AI is a technology that gives machines the ability to think like humans. AI-enabled machines can imitate humans, automate manual chores, and learn on the fly in the same way that humans can.
ML and AI have become an integral part of realizing smart transportation. In this context, using an improved deep learning model, the complex interactions among roadways, transportation traffic, environmental elements and traffic crashes have been explored. The proposed model includes two modules, an unsupervised feature learning module to identify the functional relationships between the variables and the feature representations and a supervised fine-tuning module to perform traffic crash prediction, best flight and hotel price prediction.