An Intelligent Driving Assistance System Based on Lightweight Deep Learning Models

Abstract

An intelligent driver assistance system is developed in this study, which is able to remind the drivers to turn on the head lights or wipers through situation recognition method when driving at night or on rainy days. Furthermore, the object detection results from multiple perspective views are integrated, and the surrounding object detection results are produced for collision avoidance. The system is able to alarm the drivers based on the lightweight deep learning model and the distance estimation method when surrounding vehicles are too close. Experimental results show that the proposed methods and the chosen lightweight model in our proposed system obtain reliable performance and sufficient computational efficiency under limited computing resource. In conclude, our proposed system obtains high probability to be adopted for the development of advanced driver assistance systems (ADAS). The proposed system can not only assist the driver in determining the vision ahead, but also provide an instant overview of the vehicle's surrounding conditions to enhance driving safety.