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Visual Sensors Combine for Rail Vehicle Safety

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TORONTO, Jan. 25, 2022 — Lidar system designer and manufacturer Lumibird Canada, digital technology company Thales, and the Lassonde School of Engineering at York University completed their OnTRAC project, aimed at developing, prototyping, and validating the feasibility of a sensor fusion system built on lidar technology. The program spanned 30 months. The system is designed to be integrated with autonomous rail vehicles for the purpose of obstacle detection, classification, and tracking (OCDT) in varying weather conditions.

Beginning in 2019, the partnership first performed an investigative study of the challenges and threats posed to autonomous rail vehicles, then developed a novel sensor architecture, resulting in a new prototype lidar system specifically designed for fleet rail vehicles. Safety and operational assessment — by way of in situ rail demonstrations — in typical and adverse weather conditions concluded the project last year.

Using Lumibird’s OPAL 3D lidar product family, the collaborators developed an integrated suite of vision sensors with innovative deep learning and artificial intelligence algorithms for object detection, classification, and tracking. The suite included different types of vision sensors housed in a systems architecture intended to address the stringent safety needs and performance requirements for autonomous rail operation.

The system will further support the development of safe, autonomous urban rail systems to make rail transport more efficient, less costly to operate, and capable of 24/7 functionality while minimizing accidents due to human error.

Completion of a multiyear industry/academia-led project resulted in an integrated suite of different vision sensors (especially a scalable, 3D lidar design), with deep learning and AI algorithms for object detection, classification and tracking in a systems architecture that addresses the stringent safety needs and performance requirements for autonomous rail operation. Courtesy of Lumibird Canada.


Completion of a multiyear industry/academia-led project resulted in an integrated suite of different vision sensors (especially a scalable, 3D lidar design), with deep learning and AI algorithms for object detection, classification, and tracking in a systems architecture that addresses the stringent safety needs and performance requirements for autonomous rail operation. Courtesy of Lumibird Canada.


The technology and prototype developed and demonstrated is applicable to other connecter and/or autonomous vehicle market segments, including automotive, industrial (e.g., autonomous mining), and marine.


The project was supported by the government of Ontario, through the Ontario Vehicle Innovation Network’s (OVIN’s) R&D Partnership Fund. Through OVIN, the project received 1.13 million CAD in support from the government of Ontario, with a further 1.5 million CAD in industry contribution, for a total project value of 2.59 million CAD ($2.01 million).



Published: January 2022
Glossary
lidar
Lidar, short for light detection and ranging, is a remote sensing technology that uses laser light to measure distances and generate precise, three-dimensional information about the shape and characteristics of objects and surfaces. Lidar systems typically consist of a laser scanner, a GPS receiver, and an inertial measurement unit (IMU), all integrated into a single system. Here is how lidar works: Laser emission: A laser emits laser pulses, often in the form of rapid and repetitive laser...
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