When: Thurs 23rd of Apr, 1:00pm
Where: This seminar will be presented online, RSVP here.
Speaker: Robin Vujanic
Title: Computationally Efficient Dynamic Traffic Optimisation Of Railway Systems
Abstract: In this seminar, we discuss traffic optimisation for railway systems. These can be seen as multi-agent systems with movement constraints entailing logic conditions (e.g., precedence of utilisation of specific railway tracks) and, as such, the underlying optimisation programs are large NP-hard models. To limit computational complexity, we reduce optimisation horizons. This however makes trains “blind” to the presence of each other beyond the limits of these reduced horizons, with the potential to result in deadlocking. We present an approach to address this shortcoming borrowing notions from control systems theory. We also discuss other complexity reduction mechanisms enabled by this result.
We cover examples illustrating cases where the optimisation models determine traffic patterns that, according to feedback we received form several train controllers, surpass human ability. We also briefly touch upon challenges of deploying these automation techniques in real life in a commercial setting involving a large freight network owned by Rio Tinto.
We also take this opportunity to briefly present current open opportunities for work / collaboration at RTCMA.
Bio: Robin completed his PhD at ETH Zurich, Department of Electrical Engineering and Information Technology, under the supervision of Prof. Manfred Morari. His research focuses on the application of mathematical optimisation techniques, as well as computational methods for handling large scale systems and contexts subject to uncertainty. He has been Research Fellow at the Rio Tinto Centre for Mine Automation since 2016, and became team lead for the project “Pit to Port Optimisation” in 2019.