An Accurate GNSS-Based Redundant Safe Braking System for Urban Elevated Rail Maglev Trains

Author(s)

Neto, Joao Batista Pinto ^{[1, 2]} ; Gomes, Lucas de Carvalho ^[1] ; Campista, Miguel Elias Mitre ^[1] ; Costa, Luis Henrique Maciel Kosmalski ^[1]

Affiliation

^[1] Univ Fed Rio De Janeiro, Grp Teleinformat & Automacao, BR-21941901 Rio De Janeiro - Brazil

^[2] Inst Fed Educ Ciencia & Tecnol Rondonia IFRO, Av Governador Jorge Teixeira, BR-78905160 Porto Velho - Brazil

• Document type: Journal article
• Source: INFORMATION; v. 11, n. 11 NOV 2020.
• Web of Science Citations: 0

Abstract

The association of elevated rail structures and Maglev (magnetic levitation) trains is a promising alternative for urban transportation. Besides being cost-effective in comparison with underground solutions, the Maglev technology is a clean and low-noise mass transportation. In this paper, we propose a low-cost automatic braking system for Maglev trains. There is a myriad of sensors and positioning techniques used to improve the accuracy, precision and stability of train navigation systems, but most of them result in high implementation costs. In this paper, we develop an affordable solution, called Redundant Autonomous Safe Braking System (RASBS), for the MagLev-Cobra train, a magnetic levitation vehicle developed at the Federal University of Rio de Janeiro (UFRJ), Brazil. The proposed braking system employs GNSS (Global Navigation Satellite System) receivers at the stations and trains, which are connected via an ad-hoc wireless network. The proposed system uses a cooperative error correction algorithm to achieve sub-meter distance precision. We experimentally evaluate the performance of RASBS in the MagLev prototype located at the campus of UFRJ, Brazil. Results show that, using RASBS, the train is able to dynamically set the precise location to start the braking procedure. (AU)

• FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
• Grantee: Nelson Luis Saldanha da Fonseca
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 15/24490-2 - MC2: mobile computing, content distribution, and cloud computing
• Grantee: Luis Henrique Maciel Kosmalski Costa
• Support Opportunities: Regular Research Grants