Algorithm for Railway Embedded Control Devices for Safety Maneuvres

2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON 2018): Conference Proceedings 2018
Mihails Gorobecs, Ivars Alps, Anna Beinaroviča, Anatolijs Ļevčenkovs

This study is dedicated to solve maneuvers making task while working on the station with no marshalling hump. It is a part of the project aimed at the development of intelligent safety and optimal control systems of autonomous electric vehicles and transport in general. The main maneuvers safety depends on the lack of items and other objects on the rails as well as position of turnouts. In most cases rails, occupied with other wagons, as well as wrong position of turnouts are marked with prohibiting red or blue signals of the traffic light. Authors propose an algorithm for the traffic light recognition by using Convolutional neural network (CNN) and traffic lights indicators recognition. However the situation, when locomotive needs to drive on the rails, occupied with other wagons, for example, during the manoeuvers on the railway station, can also appear. For this purpose authors have developed a CNN algorithm for the wagons recognition on the rails.

Atslēgas vārdi
electric transport, microcontroller, convolutional neural network, railway, traffic light, locomotive braking system, safety, object recognition
DOI
10.1109/RTUCON.2018.8659818
Hipersaite
https://ieeexplore.ieee.org/document/8659818

Gorobecs, M., Alps, I., Beinaroviča, A., Ļevčenkovs, A. Algorithm for Railway Embedded Control Devices for Safety Maneuvres. No: 2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON 2018): Conference Proceedings, Latvija, Riga, 12.-13. novembris, 2018. Piscataway: IEEE, 2018, 498.-502.lpp. ISBN 978-1-5386-6904-4. e-ISBN 978-1-5386-6903-7. Pieejams: doi:10.1109/RTUCON.2018.8659818

Publikācijas valoda
English (en)