Volume 10, Issue 1 (6-2023)                   IJRARE 2023, 10(1): 18-28 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Haghbin M, Safaiy F, Mahmoodi V. Practical Modeling of Existing Trains in the Shiraz Metro Using Neural Networks and PID-Fuzzy Controller for ATO System Implementation. IJRARE 2023; 10 (1) :18-28
URL: http://ijrare.iust.ac.ir/article-1-317-en.html
Shiraz Urban Railway Organization
Abstract:   (476 Views)
Transportation optimization is considered one of the main aspects of development in smart cities nowadays. Urban rail transport systems, as one of the key elements of passenger movement in large cities, have witnessed significant growth and advancement in utilizing modern knowledge to provide services to passengers over the years. The existence of sufficient infrastructure and the importance of better service provision to passengers have led these systems to always stay at the forefront of recent advancements in data analytics and artificial intelligence. Automatic Train Operation (ATO) is one of the infrastructures currently being implemented in urban trains worldwide, and its quality heavily relies on the accurate analysis of train status and signaling systems. This article aims to extract practical data from the movement of trains in the Shiraz metro, model it using a neural network, and then propose a new methodology for simulating and implementing the ATO system in urban trains through the design of a Fuzzy-PID controller.
Full-Text [PDF 925 kb]   (221 Downloads)    
Type of Study: Applicable | Subject: Electrical railway

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | International Journal of Railway Research

Designed & Developed by : Yektaweb