Grant: Collaborative Research and Development Grants

Precise, effectual railway inspection practices are necessary to facilitate the growing demand for safe and efficient urban metro systems in cities around the world today. In Canada alone, railway systems covers 60,000 km of main track-line, and transport 75 million people as well as $250 billion worth of goods each year. With such a high number of commuters relying on rail transit, it is evident that safety is a top priority in organizing public transportation systems; as the majority of derailment accidents and collisions are due to defects in the tracks, careful inspection and maintenance of railway infrastructure are necessary and regular tasks. However, current railway inspection methods rely heavily on manual work in this area, which is wasteful of both resources and time. To address this issue, the proposed research aims to develop a new remote sensing system specifically designed for the automatic inspection of railway assets. The proposed inspection system is based on a compact light detection and ranging scanner mounted on a moving vehicle, capable of densely measuring whole railway corridors in 3D with sub-centimeter accuracy at high speeds. For the past 8 years, we have conducted research to develop new technologies that automate the analysis of lidar data, in order to address the infrastructure safety concerns. In this study, we propose to extend this research, in partnership with Thales Canada, to develop state-of-the-art remote sensing technologies and algorithms for reconstructing accurate railway network models, which are attributed with structural, spatial, and contextual information about railway tracks and wayside objects, for comprehensive route and infrastructure documentation and assessments. The implemented system will not only increase the accuracy of track inspection, so as to prevent any potential disastrous railway accidents, but will also cut down on costs and service disruptions. Furthermore, the employed system will enable optimization of railway operations and maximize efficiency, consequently reducing the carbon footprint of Canada's railway systems. Finally, such automated track inspection technology will place Canada at the forefront of railway development and industries.