Title
Real-Time Embedded Vision System for the Watchfulness Analysis of Train Drivers
Abstract
AbstractRailways safety regulations require the drivers acting on a pedal to signal that they are awake and vigilant. This implies a noticeable biomechanical load on the driver. In this work, we propose an embedded computer-vision system that, using a single camera placed on the cockpit of a train, analyzes the driver’s watchfulness by monitoring gaze and eyelid blinking. The proposed system provides a consensus to the control logic of the train, which replaces the action on the pedal. The system copes with the peculiar conditions of a train’s cabin, such as variable illumination, the variability of the driver’s face image and presence of more than one people in the cabin. At the same time, it accounts for the constraints posed by the international regulation (Safety Integrity Level IV) and customer specifications, which poses limitations on the hardware selection. The paper presents the design and evaluation of this system. The former includes the hardware selection and the algorithm development, whereas the latter includes preliminary tests for tuning the algorithm and final tests in real operating conditions for the evaluation of the system. The results show that the systems always correctly detects the driver’s watchfulness and, importantly, it does not report false positives. As such, it can be used to avoid the driver’s action on the pedal and reducing the biomechanical load.
Year
DOI
Venue
2021
10.1109/TITS.2019.2955787
Periodicals
Keywords
DocType
Volume
Vehicles, Face, Cameras, Monitoring, Biomedical monitoring, Robustness, Amplitude modulation, Computer vision, drowsiness, watchfulness estimation, face tracking, PERCLOS, driver monitoring
Journal
22
Issue
ISSN
Citations 
1
1524-9050
0
PageRank 
References 
Authors
0.34
0
5