Deep Learning-based Human Vehicle Interface for Smart Golf Cart

This paper proposes a system in which a golf cart recognizes and tracks a user using a deep learning algorithm. Existing tracking golf carts use image processing algorithms or wearable sensors. However, image processing algorithms have low user recognition and tracking capabilities. In addition, the recognition and tracking system using a wearable sensor has a problem that requires an additional wearable sensor. We propose a non-attached smart golf cart using a deep learning algorithm to solve this problem. Deep learning object detection and classification algorithms are used to detect people and hands and recognize gestures in the detected hands. The golf cart performs user recognition, tracking, and human vehicle interface(HVI) by using the box of people and hands and gesture information. This paper verifies the algorithm on the golf cart.