Vehicles are a means of transportation that have existed from ancient times until now, many people use vehicles such as cars and motorbikes. Enumeration of types and numbers of vehicles is carried out to collect traffic data information. In obtaining data parameters for the number of vehicles, manual calculations are usually prone to errors and take a lot of time and energy. The application of Artificial Intelligence such as object detection is a field of computer vision. In intelligent transportation systems, traffic data is the key to conducting research and designing a system. To overcome the problem, researchers carried out object tracking using the You Only Look Once (YOLO) v8 algorithm to detect the type and count the number of vehicles. The methodology applied is the AI Project Cycle stages which use problem scoping, data acquisition, data exploration, modeling, and confusion matrix evaluation. The results of the confusion matrix evaluation obtained an accuracy level of 89%, precision of 89%, recall of 90% and a weighted comparison of precision and recall obtained an F1-Score value of 89%. Thus, the You Only Look Once (YOLO) v8 algorithm is accurate enough to detect object tracking to calculate vehicles.