Track & trackside
Similar issues in space exploration Researchers in robotic space exploration have for more than two decades been working on similar issues to ensure the safety of robotic exploration vehicles working in unstructured and hostile environments. A key to this is to provide the driver with visual and auditory inputs on what is happening in front, to the side and behind the train and sharing these views and auditory signals with the PICOP. Everyone is used to having a version of this equipment in their car with rear- viewing cameras and proximity auditory sensors. However, at night and during inclement weather conditions, most motor vehicle vision systems produce noisy and inconclusive results. To address this need, thermal InfraRed imaging needs to fused with 3D range information and ultrasonic systems so that drivers have full situational awareness of the dangers around them
whilst communicating this with the PICOP. Systems have been developed for the
coal mining industry that employ RFID detection within a 100m radius so that the PICOP and driver can be notified on an individual basis if anyone tagged is within dangerous proximity of the train. All the command and control aspects of the telecommunications have been thoroughly tested through systems for IFF/AIS (identification of friend or foe/automatic identification system). An existing alternative developed by the German Aerospace Centre, DLR is RCAS, as it seems to provide many of the aspects required by a PICOP advising of oncoming trains.
Robotic systems
Robotic systems rely on vision coupled with 3D range information to navigate in complex environments and motor vehicle
Figure 2. IC3D system © Cybula® 2011 The resultant fused vision system also has other potential applications such as minimising train-person collisions, virtual train coupling and identifying trespass when it occurs and cable theft.
collision avoidance systems use somewhat similar approaches. Surprisingly, this has not yet happened in the rail industry. The consortium plans to develop such a prototype system and test them in appropriate environments. An example of a range dataset of a typical train environment is shown taken from a terrestrial lidar [Fig.1] while a 3D model of a moving person can be seen in Fig.2 above.
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Professor Jan-Peter Muller, UCL Mullard Space Science Laboratory, Blue Sky Imaging Ltd and i3DR Ltd); Nicholas Bantin (IS Instruments Ltd & i3DR Ltd); Tom Jackson (York University & Cybula Ltd)
February 2014 Page 69
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