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Advanced Data Analytics in Transport

Posted by: data61

February 11, 2015

How can we provide transport policy makers and operators with targeted and timely tools that utilise the ubiquitous data generated from road traffic?

How can we extract new insights from existing data in transport, such as:

  • Monitoring the entire traffic network, including suburban streets, and providing quantitative measures of operational performance?
  • Evaluating transport projects in terms of impact on traffic demand and distribution?
  • Quantifying and resolving the impact of traffic incidents?
  • Influencing traveller behaviour through real-time information?


Data61’s Approach

Data61 is developing and applying new machine learning techniques with transport modelling tools, creating:

  • Integrated traffic databases, fusing multiple private and public sector sources
  • Comprehensive machine learning libraries for traffic data analytics
  • Large-scale transport modelling platforms.



Data61’s machine learning researchers are building advanced data analytic tools, enabling safer, quicker, and smarter analysis of transport networks.

  • Comprehensive evaluation of transport policy, project and pricing schemes for large-scale metropolitan areas
  • Solution-oriented, practical, dynamic traffic pattern analysis & real-time prediction
  • Multi-modal data fusion, integrating social network feeds to highlight abnormal traffic patterns.


Industry Engagement

Data61 is working with public and private sector organisations to improve planning, design, operation and maintenance of urban road networks for passenger and freight traffic.

Previous work in the field

This project builds on Data61’s ADAIT infrastructure, and relates to a number of other projects undertaken by our research team, including:

  • Intelligent Transport Systems (ITS): travel time prediction, incident prediction, correlation between travel time and incident, etc.
  • RMS Key Road Performance Report: fuse RMS data from multiple sources to produce meaningful contents and support interactive user interface.
  • Sydney CBD Mobility Modelling: quantify the impact of a light-rail construction and operation in the Sydney CBD on traffic flows. This project developed the state-of-the-art transport zoning method and origin-destination demand modelling tool, which are integrated with existing traffic assignment models.
  • TrafficWatch: detect traffic incident from social media, classify incident and provide incident impact prediction
  • Managed Motorway: an integrated motorway control that uses coordinated ramp-metering and active speed management for managing motorway congestion. Case studies presented for the Kwinana Freeway in West Australia and the M4 Motorway in Sydney


2014 RMS project – Key Roads Performance Report.

Awards and media exposure

Our research team has gained excellent awards and media attention, including:

ITS Australia Award
Chen Cai accepting the Research Academic Award at the 2014 National ITS Awards

City-scale Traffic Simulation Platform in Sydney


People: Aditya Menon, Chen Cai, Fang Chen, Felipe Trevizan, Hoang Nguyen, Ronnie Taib, Tao Wen, Tuo Mao, Weihong Wang, Xu Yan, Zelin Li, Zhang Li