Anti-Fatigue and Collision Avoidance Systems for Intelligent Vehicles with Ultrasonic and Li-Fi Sensors

Abstract

Intelligent vehicles can assist the drivers to improve the safety, comfort, sustainability and efficiency. Intelligent vehicles use emerging technologies in modeling, localization, motion control, and machine learning, which have become a research focus for many worldwide academy and industry institutes. However, there is still much open research challenge in technologies as well as collision detection and obstacles avoidance. In this work, we investigate how to effectively help drivers overcome the fatigue driving and avoid collisions. By leveraging the existing, Ultrasonic Sensor, Infrared (IR) Sensor and Li-Fi, Vehicle-to-Vehicle (V2V) Communication and machine learning technologies, we develop the Anti-Fatigue Decision Tree, Anti-Fatigue Detection and Enhanced Collision Avoidance Systems to accurately evaluate the current situation of the drivers and vehicles, and make timely response. Our prototype testing and analysis show that the proposed techniques are feasible and cost-effective.