A/Professor Dong Ngoduy

A/Professor Dong Ngoduy

Associate Professor in Transport Engineering
Department of Civil Engineering
Room 102, 23 College Walk (B60), Clayton Campus

Dong is an associate professor in transport engineering and the recipient of the UK Research Council (EPSRC) Advanced Fellow Award (2011-2016) in the area of Connected and Autonomous Vehicles. Dong Ngoduy obtained his PhD in traffic flow theory and simulation from the Technical University of Delft, the Netherlands (TU Delft) in 2006. He worked for the Institute for Transport Studies, University of Leeds, UK until 2017 in the role of research fellow-associate professor in Intelligent Transport Systems, then chaired the Conneted Traffic Systems Lab at the University of Canterbury, NZ before joining Monash University. Dong does research in Connected and Autonomous Vehicles, Traffic Flow Theory and Simulation, Data Fusion and Urban Network Optimization. His current research ambition is to build a smart city research platform which innovates, synergizes, and advances theories and technologies commensurate with the smart transport infrastructure management in mega cities with multi-modal transport modes whilst considering the emerging connected environment.


  • MSc in traffic engineering, Linkoping University of Technology, Sweden
  • PhD in traffic flow theory, Delft University of Technology, Netherlands


Traffic flow theory and characteristics
Traffic data fusion
Urban Network Optimization
Connected and Autonomous Vehicles

ARC (the Australian Research Council): Detailed Assessor

EPSRC (the UK Research Council): peer review college member

Transportmetrica A: associate editor

Transportmetrica B: associate editor

The Open Transportation Journal: editorial board member

Research Interests

My research interests include (but are not limited to) the understanding of how multi-modal traffic flow systems operate, applications of AI and machine learning to predict and monitor traffic conditions in short-term, and the investigation of the fundamental changes in the dynamics of connected transport systems.

See my google scholar

EU Horizon 2020, 3-year research project on Optimal vehicular platooning 2016-2019 (~$1.2mil)

EPSRC (the UK Research Council) 5-year Career Acceleration Fellowship on Intelligent Traffic Systems 2011-2016 (~$1mil)

Leverhulme trust research project on Noisy optimization method in Transportation Systems 2008-2010 (~$150K)

University of Leeds 4-year early career research fellowship on Real-time monitoring of freeway networks using multi-sensors data 2006-2010 (~$400K)




Trinh Xuan Sy
Real-time urban traffic flow estimations using multiple data sources
2018 to 2021

Tran Quoc Cong
Optimal charging locations for EVs in heterogeneous urban networks
2019 to 2022

Shang Jiang
AI appliations for large-scale urban transport management
2019 to 2022

Mansour Foroushani
Multi-modal network transmission model
2019 to 2022

Julie Li
Modelling lane changing process under connected environment
2020 to 2023

Hongyu Guo
Machine learning for multi-lane traffic dynamics using connected vehicle data
2019 to 2022

Weiming Zhao
Bi-level programming for intelligent intersection control
2016 to 2019

Dana Abudayyeh
Bi-level optimization for signal timings in urban networks under disruptions
2016 to 2019

Admeh Afzal
Real-time traffic enrouting using Kalman Filters
2011 to 2015

Tung Phan
Optimal control of autonomous vehicles dynamics on multi-lane roadways
2018 to 2021

Tenglong Li
Modelling traffic dynamics containing mixed connected and human driven vehicles
2018 to 2021

The Anh Hoang
Development of real-time Signal Control Framework for mixed traffic in Urban areas
2020 to 2023

Research fellow

Tony Jia
Modelling Connected and Autonomous vehicles dynamics
2014 to 2016

Seunghyeon Lee
Deep learning on traffic estimation problems
2017 to 2019

Teaching Commitments

  • civ 2282 - Transport and Traffic Engineering
Last modified: 17/03/2021