Professor Le Hai Vu

Professor Hai Vu

ARC Future Fellow, Director of Research Training, Professor in Transport Engineering
Department of Civil Engineering
Room 103, 23 College Walk (B60), Clayton Campus.

Hai L. Vu is a Professor and Australian Research Council (ARC) Future Fellow in the area of Intelligent Transport Systems (ITS). He joined Monash University in 2016 to lead the ITS research. Prior to that, he spent 5 years at the University of Melbourne and 11 years at Swinburne University of Technology where he has had established and led the Intelligent Transport Systems Lab in a joint partnership with VicRoads. He has over 18 years experience as an academic and researcher.

 

Qualifications

  • B.Eng./M.Sc. (Elec. Eng.), Technical University of Budapest (TUB), Hungary.
  • Ph.D. (Telecomm.), Technical University of Budapest (TUB), Hungary.
  • Diploma (University Teaching), Melbourne University.

Expertise

Intelligent transport systems (ITS): traffic monitoring, control and management, connected and autonomous vehicles (CAVs).
Modelling and design of complex networks: traffic theory, travel demand and behaviour modelling, stochastic optimisation.
Network modelling and analysis: strategic models, dynamic traffic assignment, multimodal transport.
Deep Learning: applying AI to transportation applications.
IoT and big data: data analytics and visualization for transportation applications.

Sky News interview on driverless cars

Research Interests

My research interest include monitoring, modelling, performance evaluation and design of complex networks (e.g. data and transportation networks), stochastic optimization and control with applications to connected autonomous vehicles (CAVs), intelligent transport systems (ITS) and smart cities.

Some of my research projects can be found below where I am currently looking to recruit new PhD students to join. The sample publications give some insights into, but do not define the research scope of that project. If you are interested in doing research in any of these projects, please contact me at the above email address.

Research Projects

Current projects

Integrated network management and control strategies to combat urban congestion

Smart use of real-time information provided by intelligent transport systems can ease urban congestion. While sensing and communication technologies appear to be mature, there remain fundamental mathematical challenges in designing a low-cost distributed system. This project will develop a mathematical framework for designing and analysing a distributed mechanism that predicts and wirelessly disseminates urban road traffic congestion. Such a mechanism couples the communication, prediction and route selection policy to load-balance traffic in urban networks.

Relevant sample publications:
G. van de Weg, H. L. Vu, A. Hegyi and S. Hoogendoorn, “A hierarchical control framework for coordination of intersection signal timings in all traffic regimes,” IEEE Trans. on ITS (T-ITS), accepted April 2018.

T. Le, H. L. Vu, N. Walton, S. S. P. Hoogendoorn, P. Kovacs and R. N. Queija, “Utility optimization framework for a distributed traffic control of urban road networks,” Transportation Research Part B: Methodological (TR-B), 105():539-558, Nov. 2017.

T. Le, P. Kovacs, N. Walton, H. L. Vu, L. L. H. Andrew and S. S. P. Hoogendoorn, “Decentralized Signal Control for Urban Road Networks,” Transportation Research Part C: Emerging Technologies (TR-C), 58():431-450, Sept. 2015.

H. L. Vu, S. P. Hoogendoorn, E. Smits, M. Panda, H. Zurlinden, V. Vong and P. Lam, “The Integrated Network Management (INM) Framework,” in Proc. of the 23rd ITS World Congress, Melbourne, Australia, 10–14 Oct. 2016.

Future mobility involving connected and autonomous vehicles (CAVs)

This project investigates the different aspects of traffic and transportation networks where emerging technology (e.g. connected vehicles or direverless cars) and their future mobility services (e.g. ride sharing, MaaS) are deployed and used.

Relevant sample publications:
S. Stebbins, M. Hickman, J. Kim and H. L. Vu, “Characterising Green Light Optimal Speed Advisory Trajectories for Platoon-Based Optimisation,” Transportation Research Part C: Emerging Technologies (TR-C), 82():43-62, Sept. 2017.

D. Jia, D. Ngoduy and H. L. Vu, “A multiclass microscopic model for heterogeneous platoon with vehicle-to-vehicle communication,” Transportmetrica B: Transport Dynamics, accepted Jan. 2018.

Transportation network and demand modelling

This project develops network models for large-scale transportation networks that underpins the development of smart real-time decision support systems (DSS) to support the design, planning and operation of the transport networks. In particular we focus on the availability of information and their impact on the user’s behaviour and efficiency of the overall network.

Relevant sample publications:
N. H. Hoang, H. L. Vu, M. Panda and H. K. Lo, “A linear framework for dynamic user equilibrium traffic assignment in a single origin-destination capacitated network,” Transportation Research Part B: Methodological (TR-B), available online, 2017.

D. Ngoduy, N. H. Hoang, H. L. Vu and D. P. Watling, “Optimal queue placement in dynamic system optimum solutions for single origin-destination traffic networks,” Transportation Research Part B: Methodological (TR-B), 92():148-169, Oct. 2016.

L. Ravner, M. Haviv and H. L. Vu, “A strategic timing of arrivals to a linear slowdown processor sharing system,’’ European Journal of Operational Research, 255(2):496-504, Dec 2016.

AI, Machine Learning and Data analytics for transportation applications

This project aims to capture and understand the mobility patterns and their evolution within a large-scale urban road network using the available heterogeneous data sources.

Relevant sample publications:
T. Anwar, C. Liu, H. L. Vu, Md. S. Islam and T. Sellis, “Capturing the Spatiotemporal Evolution in Road Traffic Networks,” IEEE Trans. on Knowledge and Data Engineering (TKDE), available online, Jan. 2018.

T. Anwar, C. Liu, H. L. Vu and C. Leckie, “Partitioning road networks using density peak graphs: Efficiency vs. accuracy,’’ Information Systems, 64():22-40, 2017.

P. Krishnakumari, T. Nguyen, L. H. Ottens, H. L. Vu and H. van Lint, “Traffic congestion pattern classification using multiclass active shape models,” Transportation Research Record, Jan. 2017.

IoT, Smart Cities and data communication for ITS

This project focuses on the infrastructure required for enabling and operating a smart systems including intelligent transport systems, smart cities and any IoT systems. The underpinning wireless data communication and network design will be modeled and investigated. The focus will be on evaluating the performance, planning and optimal design of such a network.

Relevant sample publications:
S. Pokhrel, M. Panda and H. L. Vu, “Fair Coexistence of Regular and Multipath TCP over Wireless Last-Miles,” IEEE Trans. on Mobile Computing (TMC), available online, May 2018.

S. Pokhrel, M. Panda and H. L. Vu,“ Analytical Modeling of Multipath TCP over Last-Mile Wireless,’’ IEEE/ACM Trans. on Networking (TON), 25(3):1876-1891, Feb. 2017.

H. P. Luong, M. Panda, H. L. Vu and B. Q. Vo, “Beacon Rate Optimization for Vehicular Safety Applications in Highway Scenarios,’’ IEEE Trans. on Vehicular Technology (TVT), available online, Aug. 2017.

H. P. Luong, M. Panda, H. L. Vu and B. Q. Vo, “Analysis of Multi-hop Probabilistic Forwarding for Vehicular Safety Applications on Highways,’’ IEEE Trans. on Mobile Computing (TMC), available online, June 2016.

ARC Discovery Grant (DP180102551 2018-2020) with K. An, $294K AUD.
ARC Discovery Grant (DP1095103, 2013-2015) with L. L. Andrew, Y. Nazarathy, S. H. Low and M. Mandjes, $300K AUD.
ARC Future Fellowship (FT120100723, FT2, 2012-2016), $693K AUD.
ARC Discovery Grant (DP130100156, 2010-2012) with L. L. Andrew, $150K AUD.
ARC Discovery Grant (DP0557660, 2005-2007), $90K AUD.

Cisco CCRI grant (2013-2014), with G. Armitage, $92K USD.
FICT Dean’s Collaborative Grants (2007-2008), $35K AUD.
Swinburne LTPF Funding for Educational Innovation (2007-2008), $30K AUD.
Swinburne Research Development Scheme (RDS) Grant (2006-2007), $20K AUD.
Melbourne University Research Grant, (2004-2005), $16K AUD.
Melbourne University, E&E Department  Early Career Researcher Grant, (2003-2004), $10K AUD.

Supervision

PHD

Tarique Anwar

Neda Taherifar

Tung Minh Le

Hien Phuong Luong

Shiva Pokhrel

Nam Hong Hoang

Tarikul Islam

Tin Nguyen

Cuong Nguyen

Atousa Tajaddini

Homayoun Hamedmoghadam-Rafati

Punthila Jayarathne

Loan Do

Sajjad Shafiei

Last modified: July 23, 2018