Backplane System Technologies discusses the use of driverless technology for trams.
In the heart of Australia’s Pilbara – the mining region located in the country’s western coast – lives the world’s heaviest robot. The robot is two kilometres in length and takes the form of an autonomous freight train. Without a human conductor present, the train relies on Artificial Intelligence (AI) -powered cameras and machine learning algorithms[1].
The development of the robot is a testament to a larger movement within the transportation industry. Autonomous trains, also known as driverless trains, are quickly gaining relevance. However, with all new technology, comes the apprehension of its viability.
The upcoming NRU-220S Series, powered by NVIDIA Jetson AGX Orin, sets new standards in computational density, energy efficiency, and AI inferencing for edge devices – allowing for greater processing capabilities[2].
Functioning as an all-in-one solution for AI NVR real-time inference and video transcoding, this hardware features a fanless design and the ability to operate over a wide temperature range, making it suited for deployment in autonomous vehicles.
- Enhancing safety and security with real-time surveillance
In the rail transport industry, security encompasses a spectrum of challenges, from potential passenger safety breaches to the risk of disruptions in critical infrastructure. In the context of autonomous trains, concerns about compromising passenger safety are particularly evident.
Leveraging multiple high-quality IP video streams, the NRU-220S enables real-time video processing, providing operators with the capability to remotely monitor diverse elements such as train surroundings, track conditions, and passenger areas.
- Optimising performance with predictive maintenance
Downtime poses a threat to productivity, and in the fast-paced world of public transportation, having all trains available is essential to maintaining smooth operations at tram stops and stations.
The NRU-220S hardware’s capabilities enable predictive maintenance for autonomous trains, reducing downtime and repair costs by analysing sensor data to anticipate maintenance prior to issues arising.
- Facilitating seamless connectivity
In the deployment of driverless trains, effective communication is pivotal for a successful operation. In the absence of a human driver, the train must establish seamless communication with control centres and other trains across the network to maintain a cohesive flow.
The hardware’s diverse connectivity options, featuring high-speed Ethernet ports, play a crucial role in enabling this seamless communication, fostering efficient coordination with signalling systems, control centres, and other trains on the network.
- Efficiency in power consumption
The rail transport industry functions within a competitive business landscape, where even minor enhancements in fuel efficiency or fluctuations in fuel prices can exert significant influences on profitability and market competitiveness.
The system includes ignition power control, which can be important for in-vehicle deployment. It ensures that the system can efficiently manage power when starting and shutting down a vehicle, optimising energy usage.
In an era marked by burgeoning urbanisation, climate concerns, and other factors that exert pressure on public transportation, the rail industry demands innovative solutions. Much like the autonomous train in Pilbara, the use of such technologies couldn’t have been achieved without the implementation of AI-processing hardware like the NRU-220S series.
For additional information about the NRU-220S series, Backplane System Technologies, a provider of industrial PCs, offers a specialised sourcing team dedicated to identifying the most suitable components to meet your specific rail needs.
Discover the next generation of AI-processing hardware for rail. Explore the NRU-220S – learn more at: https://www.backplane.com.au/product/nru-220s/
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