We have been selected as finalists of the ITS Australia Awards 2021 in two categories: Excellence in Research & Development and Excellence in Transport Data.
Estimating the Impact of Electric Vehicles Across Transport and Energy Systems (Excellence in Research & Development category): University of Technology Sydney Estimating the Impact of Electric Vehicles Across Transport and Energy Systems UTS collaborated with the Australian Energy Market Operator using data from Transport for NSW, to deliver a new transdisciplinary approach for estimating the impact of future Electric Vehicle adoption. The novel approach uses a joint transport and energy consumption modelling approach, that connects the transport and energy sectors. The project estimated the electric vehicle adoption impact on consumer waiting times, traffic congestion and energy demand across multiple EV uptake scenarios.
Next Generation of Digital Twins (Excellence in Transport Data category): UTS Data Science Institute has been working in the last years on building the Sydney Real-Time Digital Twin Platform, integrating at once several types of data sources such as all the city 3D layout with top layers like the public transport movement in real-time, transport simulation for incident scenario management in real-time, water pipes layout via IoT sensing data transmission and air quality real-time transmission from monitoring stations in Sydney.
We have been selected as finalist of the IoT Awards 2021 in Smart Cities category.
Next Generation of Digital Twins (Smart Cities category): UTS Data Science Institute has been working in the last years on building the Sydney Real-Time Digital Twin Platform, integrating at once several types of data sources such as all the city 3D layout with top layers like the public transport movement in real-time, transport simulation for incident scenario management in real-time, water pipes layout via IoT sensing data transmission and air quality real-time transmission from monitoring stations in Sydney.
[9th of June 2021] FMlab has organised a joint half-day seminar together with the Monash University Monash Institute of Transport Studies, Faculty of Engineering on the topic of AI in transportation Applications. List of presentations delivered:
Adriana-Simona Mihaita, Zac Papachatgis, Marian-Andrei Rizoiu, Graph modelling approaches for motorway traffic flow prediction, IEEE ITSC2020.
The study has been applied on the M7 motorway in Sydney using 36.3 million traffic flow records for prediction.
Yuming Ou, Adriana-Simona Mihaita, Fang ChenDynamic Train Demand Estimation and Passenger Assignment, IEEE ITSC2020.
The study has been done on the Sydney Train network with 175 stations, 506 platforms and has estimated and re-calibrated 2.9 million OD matrices to be used for passenger assignment on each platform
The Transport and A.I. Research forum saw around 100 representatives from government, academia and industry joining forces here at University of Technology Sydney for presenting their ongoing works and future needs in terms of data processing, concerns, AI needs, etc.
The event was opened by the NSW Chief Scientist and Engineer, Hugh Durrant-Whyte who insisted on the usage of Deep Learning and AI technology to be applied not independently, but together with causal models in order to clearly understand why specific disruptions happen in the transport network, followed by Distinguished Prof. Fang Chen which debated by we need data-driven analytics and how these have been applied in the Data Science Institute at UTS. The session continued with presentations from Pascal Labouze, Executive Director of Operational Systems at Transport for NSW who insisted that there is huge need to go towards more data-integrated centralized approaches for managing transport, equally supported by the Director of Traffic management and Safety, Ben Hubbard in ACT who highlighted that a similar approach is currently undertaken in Canberra. Jeff Sharp from Transurban presented some of the data-driven solutions being used for monitoring the City Link in Melbourne and multiple data integrations for incident detection while V/line’s representatives Unal Altay and Andres Hernandes showcased a data-driven train analysis platform for incident management, real-time train line performance monitoring and punctuality prediction developed in partnership with UTS.
Second session saw presentations from both government and industry with specific case studies where data science has been applied successfully for solving some of ardent problems. The Roads and Maritime Services in Sydney is moving along the data driven approaches by creating a dedicated team to analyse, integrate and predict traffic counts collected from all around the city of Sydney under the supervision of David Scott, while Sydney Trains have already deployed advanced Machine learning systems in collaboration with UTS to detect train track defects automatically and learn from previous locations where these defects have appeared (work presented by Ian Greager, Principal Manager in Sydney Trains). The session saw real-life applications from Christian Porter - Group Executive General Manager at the Downer Group on how data has helped to plan new services (such as on-demand buses and ferries), followed by Paul Rybicki from DSpark who showcased the value of utilising mobile data for transport management and crowd behaviour analysis, and TomTom’s Jennifer Loake who highlighted ongoing advancement techniques in both Lidar scanning and traffic routing solutions. The event was closed by the event’s sponsor – Intel and its Solution Architect Peter Kerney who showcased some of the software and hardware capabilities that can support advanced applications of data-driven and AI solutions.
Finally, Data Arena demonstrations have been put in place to present the current real-time traffic monitoring platforms and simulation models that the FM-lab has been working on.
Join our inaugural event highlighting Artificial Intelligence solutions for transport. Click here to register.
Data-driven artificial intelligence has become an important part of modern decision making processes, including in transportation, where the abundance of data represents a challenge for transport agencies and research scientists alike.
The objective of this Research Forum is to link government, industry and academic professionals who are interested in or delivering innovative data-driven, artificial intelligence and/or cloud-based solutions to emerging transport problems. Together, we will explore the practical use of cutting-edge technologies to deliver efficient, evidence-based transport planning for Australia.
Key questions that will be explored in the Forum include:
Date and Time:
Fri., 6 December 2019
8:00 am – 2:00 pm AEDT
Aerial UTS Function Centre
15 Broadway 9
#Building 10, Level 7
Ultimo, NSW 2007
This Event is Sponsored by Intel Corporation
Dr. Mihaita was invited by the Prime Minister Scott Morrison to attend “2019 Prime Minister’s Prizes for Science” at the Parliament House in Canberra on 16th of Oct 2019
[30 June 2019] Mihaita, A.S., Li, H., He, Z., Rizoiu, M.-A. (2019) Motorway Traffic Flow Prediction using Advanced Deep Learning, Proceedings of the 22nd Intelligent Transportation Systems Conference (ITSC'19) Auckland, New Zealand. 27-30 October, 2019. Preprint link
[27 June 2019] Dr. Mihaita delivered a talk in the "Science in the city" talk series event organized by Research Director Simon Dunstall of Data61, together with Arthur Maheo from Monash university, Fiona Calvert from the Department of Transport Victoria. Event link of future series to come: https://lnkd.in/gy5k6Gv
[18 June 2019] FTMlab started a collaboration with NSSN (NSW Smart Sensing Network) on Air quality investigation for the city of Sydney.
[13 June 2019] Prof. Fang Chen, Dr. Simona Mihaita and A/Prof. Adam Berry attended a national workshop organized by Fortescue Metal Group in Perth, together with representatives from: Queensland University of Technology, Australian National University, Curtin University, University of Western Australia, Edith Cowan University. The main purpose is the building of the new Karratha Living Lab with integrated autonomous and connected vehicle systems.
The Future Tranport Mobility Group is actively searching to recruit 2 new full-time PhD students (domestic or international) to be working on the following Topics:
9th of May 2019: Dr. Mihaita and Dr. Adam Berry met with Transgrid representatives in an official visit to Techlab given by Ray Kirby (Tech Lab Director) with the purpose of establishing future collaborations and projects in a DXC Digital Transformation Centre. Dr. Mihaita delivered a presentation on the UTS Australian Institute of Data Excellence capabilities in data analytics and artificial intelligence, while Dr. Berry provided insights on energy research capabilities.
[14 May 2019] Dr. Mihaita and Dr. Fang Chen received the National Research Foundation from Singapore for discussing future collaboration discussions between UTS and Singaporean research Institutions on topics such as Urban Mobility, CyberSecurity and Artificial Intelligence. The presentation workshop was delivered by:
[11 April 2019] Dr Mao, Dr. Mihaita, Dr. Yang Wang and Dr. Liang have attended the Tech Lab event and presented Demos of our ongoing work on the transport modelling, data driven prediction and also water pipe failure prediction.
[30 April 2019] Dr Mihaita, Dr. Fang and Dr. Kun Yu received a DXC visit and delivered a presentation of capabilities in the Data Arena.
The Special Interest Session SIS925 on “Crowd movement analysis and modelling” has been accepted by the ITS World Congress organisers. Dr Mihaita will organise the session with the following confirmed speakers (2 more to be added):