Smart Driver Behavior Recognition and 360-Degree Surround-View Camera for Electric Buses

Abstract

The automotive industry’s focus on driver-oriented issues underscores the critical importance of driver safety. This paper presents the development of advanced driver assistance system (ADAS) algorithms specifically tailored for an electric bus (e-bus) to enhance safety. The proposed approach incorporates two key components: a 360-degree surround-view system and driver behavior recognition utilizing the You Only Look Once V5 (YOLO_V5) method. The adoption of YOLO_V5 in ADASs enables rapid response by processing multiple class probabilities and region proposals within an image instantaneously. Additionally, ADAS implementation includes an image processing-based surround-view system utilizing OpenCV. In order to evaluate the performance of the proposed algorithms regarding a smart e-bus, comprehensive experimental studies were conducted. The driver behavior recognition system underwent rigorous testing using various images captured by an onboard camera. Similarly, the surround-view system’s performance was verified in diverse driving scenarios, including regular driving, parking, and parking in near-to-line situations. The results demonstrate the viability and effectiveness of the proposed system, validating its potential to significantly improve driver safety in electric buses. This paper provides a comprehensive overview of the work accomplished by emphasizing the specific contributions of the 360-degree surround-view system, driver behavior recognition using YOLO_V5, and the experimental validation conducted for an e-bus.