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A $4 million Australian research project will look to automate the construction of embedded rail track (ERT), with the potential to apply the technology in the construction of heavy-haul and high-speed rail.
The project has received $1.5 million in funding through the federal government’s Cooperative Research Centres Projects (CRC-P) grant scheme, as well as cash and in-kind contribution from the research partners.
Currently, ERT is only used in limited lengths due to the high cost and length of time that it takes to lay the concrete-embedded slab track. However, ERT is much safer than regular ballasted track, and with fewer components, needs less regular maintenance.
The University of Wollongong (UoW) is one of the project participants and project leader Philip Commins from UoW said the project would look to utilise advanced robotics to lay the track. Over the course of the project, the team from UoW will be looking into how this technology can be used to lay slab track with millimetre-level accuracy.
“Do you need multiple robots, or, is there another process to do this? Do you need material handling or is there another process where you remove material rather than trying to hold material, or add material in place? There’s a whole host of ideas that we’re going to be investigating to find which one works best and how do we then proceed to make this process robust in a harsh Australian environment,” said Commins.
With ERT laid in concrete, there is less room for error in construction than when construction ballasted track. In the current manual process, this need for accuracy means that track is laid in 50 metre segments. To overcome this, one area the project will explore will be how to continuously lay ERT.
“Ultimately we think that to drive down the cost the time of installation we want to do this in a continuous fashion,” said Commins. “We want to say, ‘We’re starting here today and we need to get to there by the end of today,’ and the machine ideally shouldn’t stop.”
To get to this goal, the research project will take two years to identify challenges, and find the hardware and software solutions required, as well as the needs for materials and logistics.
The project also involves the University of Technology Sydney, Downer, Embedded Rail Technology, and Antoun Civil.
Artificial intelligence (AI) will be applied to CCTV footage from cameras on the Sydney train network to detect threatening behaviours.
The trial is the result of Transport for NSW’s Safety After Dark Innovation Challenge, which sought initiatives to improve safety for women travelling on public transport.
The AI CCTV solution was proposed by the University of Wollongong’s SMART Infrastructure Facility. The software would automatically analyse real-time footage and alert an operator when it detect a suspicious incident or unsafe environment.
Lead researcher John Barthelemy said the software could be applied in a number of ways.
“The AI will be trained to detect incidents such as people fighting, a group of agitated persons, people following someone else, and arguments or other abnormal behaviour,” he said.
“It can also identify an unsafe environment, such as where there is a lack of lighting. The system will then alert a human operator who can quickly react if there is an issue.”
The project is based on PhD student Yan Qian’s research that is using computer vision across multiple cameras to improve understandings of traffic and pedestrian movements.
“We are using open-source code that tries to estimate the poses of a human being and predict if there’s a fight,” she said.
“As far as we know, nothing like this has been attempted globally. We are pushing the limits of the technology.”
Other successful projects came from data sharing platform She’s a Crowd, safety technology vendors Guardian LifeStream and Cardno/UNSW.
Minister for Transport Andrew Constance said that transport operators had an obligation to improve the experience of travelling on their networks.
“We want all our customers to feel safe on the network and it is not good enough that 9 out of 10 Australian women experience harassment on the street and modify their behaviour in response,” Constance said.
“The winners were chosen for their potential to meaningfully address real safety issues, and their ability to use creative and sophisticated new technologies to make a real difference.”