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Professor Zuduo Zheng
Professor

Zuduo Zheng

Email: 
Phone: 
+61 7 344 31371

Overview

Background

Professor Zuduo Zheng is TAP Chair (Deputy) sponsored by Queensland Department of Transport and Main Roads, and Professor in the School of Civil Engineering, a current ARC Future Fellow, and a former ARC DECRA Research Fellow. He is currently a member of the College of Experts, the Australian Research Council.

His research primarily focuses on:

  1. traffic flow theory, modelling, simulation and optimisation;
  2. understanding emerging, disruptive, and intelligent mobility technologies’ impact on traffic efficiency, traffic safety, energy consumption, vehicle emissions, etc.;
  3. developing essential theories, the foundational algorithms and analytics that can seamlessly integrate future mobilities into the existing transportation systems;
  4. establishing a new breed of control strategies tailored to maximise the power of the connected environment and vehicle automation; and
  5. complex systems modeling and the design of adaptable, controllable, resilient, and sustainable infrastructure systems (intelligent transportation systems and smart city particularly in the context of the 2032 Olympic and Paralympic Games).

He has been listed as the Top 2% of Scientists in Logistics and Transportation by Scopus & Stanford University since 2020. He has won many prestigious awards, and serves/served as editor, guest editor or editorial board member of several prestigious journals, including Transportation Research Part B, Transportation Research Part C, Analytic Methods in Accident Research , IEEE Transactions on Intelligent Transportation Systems, etc.

More information about Professor Zheng's research activities and engagements can be found here.

Availability

Professor Zuduo Zheng is:
Available for supervision
Media expert

Qualifications

  • Doctor of Philosophy, Arizona State University

Research interests

  • Traffic flow theories and operations, with a focus on emerging technologies

  • Travel behaviour, strategic transport planning and modeling, and decision making

  • Traffic operation and management for big events (e.g., Olympic and Paralympic Games)

  • Traffic safety

  • Advanced data analysis techniques (e.g., mathematical modeling, econometrics, numerical optimization) in transport engineering

  • Research on research (or meta-research)

Works

Search Professor Zuduo Zheng’s works on UQ eSpace

130 works between 2006 and 2025

1 - 20 of 130 works

2025

Journal Article

Reassessing desired time headway as a measure of car-following capability: definition, quantification, and associated factors

Parashar, Shubham, Zheng, Zuduo, Rakotonirainy, Andry and Haque, Md Mazharul (2025). Reassessing desired time headway as a measure of car-following capability: definition, quantification, and associated factors. Communications in Transportation Research, 5 100169, 1-11. doi: 10.1016/j.commtr.2025.100169

Reassessing desired time headway as a measure of car-following capability: definition, quantification, and associated factors

2025

Journal Article

Central-upwind scheme for the phase-transition traffic flow model

Chu, Shaoshuai, Kurganov, Alexander, Mohammadian, Saeed and Zheng, Zuduo (2025). Central-upwind scheme for the phase-transition traffic flow model. Journal of Computational Physics, 539 114241, 114241-539. doi: 10.1016/j.jcp.2025.114241

Central-upwind scheme for the phase-transition traffic flow model

2025

Journal Article

An integrated method based on wavelet modulus maxima and local Holder exponents for automatic phase detection and labelling of lane-changing execution

Cao, Zhuo, Zheng, Zuduo, Yildirimoglu, Mehmet and (Md. Mazharul) Haque, Shimul (2025). An integrated method based on wavelet modulus maxima and local Holder exponents for automatic phase detection and labelling of lane-changing execution. Transportation Research Part C: Emerging Technologies, 179 105285, 105285-179. doi: 10.1016/j.trc.2025.105285

An integrated method based on wavelet modulus maxima and local Holder exponents for automatic phase detection and labelling of lane-changing execution

2025

Journal Article

Integrating road network operations planning into real-time traffic management: A conceptual framework

Keblawi, Mahmud, Maripini, Himabindu, Kim, Jiwon, Hickman, Mark, Zheng, Zuduo and Yildirimoglu, Mehmet (2025). Integrating road network operations planning into real-time traffic management: A conceptual framework. Transportation Research Interdisciplinary Perspectives, 32 101525, 101525. doi: 10.1016/j.trip.2025.101525

Integrating road network operations planning into real-time traffic management: A conceptual framework

2025

Journal Article

Segment-then-refine: A general calibration framework incorporating intra-driver heterogeneity into Car-Following Models

Wang, Chengming, Jia, Dongyao, Zheng, Zuduo, Ngoduy, Dong, Wang, Wei and Wang, Shangbo (2025). Segment-then-refine: A general calibration framework incorporating intra-driver heterogeneity into Car-Following Models. Transportation Research Part C: Emerging Technologies, 176 105144, 105144-176. doi: 10.1016/j.trc.2025.105144

Segment-then-refine: A general calibration framework incorporating intra-driver heterogeneity into Car-Following Models

2025

Journal Article

Empirical research on car-following and lane-changing: Recent developments, emerging vehicle technologies’ impact, and future research needs

Ali, Yasir, Sharma, Anshuman and Zheng, Zuduo (2025). Empirical research on car-following and lane-changing: Recent developments, emerging vehicle technologies’ impact, and future research needs. Transportation Research Interdisciplinary Perspectives, 31 101368, 101368. doi: 10.1016/j.trip.2025.101368

Empirical research on car-following and lane-changing: Recent developments, emerging vehicle technologies’ impact, and future research needs

2025

Journal Article

Eco-cooperative adaptive cruise control for platoons in mixed traffic using single-agent and multi-agent reinforcement learning

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2025). Eco-cooperative adaptive cruise control for platoons in mixed traffic using single-agent and multi-agent reinforcement learning. Transportation Research Part D: Transport and Environment, 142 104658, 104658-142. doi: 10.1016/j.trd.2025.104658

Eco-cooperative adaptive cruise control for platoons in mixed traffic using single-agent and multi-agent reinforcement learning

2025

Journal Article

Developing Merging Policies for CAVs: A Policy Training Framework Combining Human Experience with Reinforcement Learning

Ma, Yingyue, Li, Ye, Zheng, Zuduo and Huang, Helai (2025). Developing Merging Policies for CAVs: A Policy Training Framework Combining Human Experience with Reinforcement Learning. IEEE Transactions on Intelligent Vehicles, 10 (5), 2977-2986. doi: 10.1109/tiv.2024.3445334

Developing Merging Policies for CAVs: A Policy Training Framework Combining Human Experience with Reinforcement Learning

2025

Journal Article

Numerical study of the non-conservative NET-RAT traffic flow model by path-conservative central-upwind schemes

Mohammadian, Saeed, Zheng, Zuduo, Chu, Shaoshuai and Kurganov, Alexander (2025). Numerical study of the non-conservative NET-RAT traffic flow model by path-conservative central-upwind schemes. Computers and Mathematics with Applications, 179, 212-228. doi: 10.1016/j.camwa.2024.12.014

Numerical study of the non-conservative NET-RAT traffic flow model by path-conservative central-upwind schemes

2025

Journal Article

Developing and validating an adaptive multi-layer vehicle trajectory reconstruction method for outlier removal

Li, Ruijie, Zheng, Zuduo, Ngoduy, Dong and Li, Linbo (2025). Developing and validating an adaptive multi-layer vehicle trajectory reconstruction method for outlier removal. Transportation Research Part C: Emerging Technologies, 171 104946, 1-33. doi: 10.1016/j.trc.2024.104946

Developing and validating an adaptive multi-layer vehicle trajectory reconstruction method for outlier removal

2025

Journal Article

Brain activity patterns reflecting security perceptions of female cyclists in virtual reality experiments

Bidgoli, Mohammad Arbabpour, Behmanesh, Arian, Khademi, Navid, Thansirichaisree, Phromphat, Zheng, Zuduo, Tehrani, Sara Saberi Moghadam, Mazloum, Sajjad and Kongsilp, Sirisilp (2025). Brain activity patterns reflecting security perceptions of female cyclists in virtual reality experiments. Scientific Reports, 15 (1) 761, 1-19. doi: 10.1038/s41598-024-81271-8

Brain activity patterns reflecting security perceptions of female cyclists in virtual reality experiments

2025

Journal Article

Performance analytics for the value chain process of international airports: a dynamic network measure with the shared and unsplittable links

Yu, Anyu, Zhou, Fan and Zheng, Zuduo (2025). Performance analytics for the value chain process of international airports: a dynamic network measure with the shared and unsplittable links. Annals of Operations Research, 351 (1), 3-33. doi: 10.1007/s10479-024-05988-5

Performance analytics for the value chain process of international airports: a dynamic network measure with the shared and unsplittable links

2024

Journal Article

A method for long car-following pair extraction and comprehensive data quality assessment: a case study using Zen Traffic Data

Li, Ruijie, Zheng, Zuduo, Ni, Daiheng and Li, Linbo (2024). A method for long car-following pair extraction and comprehensive data quality assessment: a case study using Zen Traffic Data. Transportation Letters, 17 (7), 1-20. doi: 10.1080/19427867.2024.2425514

A method for long car-following pair extraction and comprehensive data quality assessment: a case study using Zen Traffic Data

2024

Journal Article

Empirical evidence of connected environment driving on fuel consumption and emissions

Ali, Yasir, Sharma, Anshuman, Zheng, Zuduo and Haque, Md. Mazharul (2024). Empirical evidence of connected environment driving on fuel consumption and emissions. IEEE Transactions on Intelligent Vehicles, 9 (11), 7239-7250. doi: 10.1109/tiv.2024.3395500

Empirical evidence of connected environment driving on fuel consumption and emissions

2024

Journal Article

A novel mobility consumption theory for road user charging

Bliemer, Michiel C. J., Loder, Allister and Zheng, Zuduo (2024). A novel mobility consumption theory for road user charging. Transportation Research Part B: Methodological, 189 102998. doi: 10.1016/j.trb.2024.102998

A novel mobility consumption theory for road user charging

2024

Journal Article

Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2024). Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections. Transportation Research Part C: Emerging Technologies, 165 104683, 1-35. doi: 10.1016/j.trc.2024.104683

Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections

2024

Journal Article

Disability-specific factors in paratransit system continuance: implications for transportation policy and practice in low-income developing countries☆

Ekramifard, Ali, Khademi, Navid, Chaiyasarn, Krisada and Zheng, Zuduo (2024). Disability-specific factors in paratransit system continuance: implications for transportation policy and practice in low-income developing countries☆. Transport Policy, 153, 173-189. doi: 10.1016/j.tranpol.2024.05.016

Disability-specific factors in paratransit system continuance: implications for transportation policy and practice in low-income developing countries☆

2024

Journal Article

A dynamic system optimal dedicated lane design for connected and autonomous vehicles in a heterogeneous urban transport network

Ngoduy, Dong, Nguyen, Cuong H.P., Lee, Seunghyeon, Zheng, Zuduo and Lo, Hong K. (2024). A dynamic system optimal dedicated lane design for connected and autonomous vehicles in a heterogeneous urban transport network. Transportation Research Part E: Logistics and Transportation Review, 186 103562, 103562. doi: 10.1016/j.tre.2024.103562

A dynamic system optimal dedicated lane design for connected and autonomous vehicles in a heterogeneous urban transport network

2024

Journal Article

On the string stability of neural network-based car-following models: A generic analysis framework

Zhang, Xiaohui, Sun, Jie, Zheng, Zuduo and Sun, Jian (2024). On the string stability of neural network-based car-following models: A generic analysis framework. Transportation Research Part C: Emerging Technologies, 160 104525, 1-23. doi: 10.1016/j.trc.2024.104525

On the string stability of neural network-based car-following models: A generic analysis framework

2024

Journal Article

Shifting towards luxury cars: The price and environmental effects of Beijing’s vehicle lottery system and an alternative policy

Zhou, Fan, Yang, Ziying, Wu, Di and Zheng, Zuduo (2024). Shifting towards luxury cars: The price and environmental effects of Beijing’s vehicle lottery system and an alternative policy. Transportation Research Part A: Policy and Practice, 181 104012. doi: 10.1016/j.tra.2024.104012

Shifting towards luxury cars: The price and environmental effects of Beijing’s vehicle lottery system and an alternative policy

Funding

Current funding

  • 2026 - 2030
    From error-prone human driving to error-free superhuman-like self-driving
    ARC Future Fellowships
    Open grant
  • 2024 - 2028
    Safe and efficient eco-driving using connected and automated vehicles
    ARC Discovery Projects
    Open grant

Past funding

  • 2023 - 2025
    A real-time traffic signal system for safe and efficient intersections (ARC Linkage Project administered by Queensland University of Technology)
    Queensland University of Technology
    Open grant
  • 2023
    Design of a driving simulation experiment for mixed traffic using SimCCAD - Experiment A
    University of Massachusetts Lowell
    Open grant
  • 2023
    Design of a driving simulation experiment for mixed traffic using SimCCAD - Experiment B
    University of Massachusetts Lowell
    Open grant
  • 2022 - 2024
    Framework and Conceptual Solution for Integrating Road Network Operations Planning into Real-time Traffic Management
    iMove Cooperative Research Centre
    Open grant
  • 2022 - 2024
    DynaMix-FM, dynamic mixed reality environment for future mobility (ARC LIEF application led by Queensland University of Technology)
    Queensland University of Technology
    Open grant
  • 2021 - 2023
    Urban Freight Shifts
    iMove Cooperative Research Centre
    Open grant
  • 2021 - 2024
    Unifying Traffic Modelling and Safety Management for Safer and Faster Roads
    ARC Discovery Projects
    Open grant
  • 2020 - 2025
    Transport Academic Partnership 2020-2025
    Queensland Department of Transport and Main Roads
    Open grant
  • 2020 - 2025
    Transport Innovation and Research Hub
    Brisbane City Council
    Open grant
  • 2018 - 2019
    Modelling mixed traffic traditional, connected and automated vehicles
    ARC Discovery Early Career Researcher Award
    Open grant

Supervision

Availability

Professor Zuduo Zheng is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • Fundamental issues in calibrating and validating traffic flow models

  • An integrated platform of traffic flow simulation, communication simulation, and driving simulator

  • Modelling transportation systems with traditional, connected and autonomous vehicles

    Connected vehicles communicate with neighboring vehicles (V2V) and infrastructure (V2I), and automated vehicles drive themselves without the need for human intervention for some of or all the driving tasks. Recent and rapid technology advancements are transporting the concept of CAVs from science fiction to scientific fact. While the valuable information collected and communicated by CAVs provides unprecedented opportunities for optimising traffic flows, the lack of a robust, theory-based operational plan for mixed traffic flow will lead to more chaotic roads. Firstly, much of our modelling of the traffic flow and traffic operations of traditional vehicles will be obsolete at best, and dangerously misleading at worst. Secondly, for connected vehicles, driver’s response and compliance to information received is critical, e.g., the total ignorance of a driver to the information would render connectivity useless; and for automated vehicles, depending on the level of automation, drivers need to frequently switch between two different roles: as a driver to execute driving tasks, and as a supervisor to monitor the driving environment, and when needed, resume vehicular control. Previous studies have reported that automation may lead to overreliance, erratic workload, skill degradation, and reduced situation awareness. And finally, the impact of CAVs on transport systems, while revolutionary, is also evolutionary. For the foreseeable future, traditional vehicles will need to co-exist with CAVs in a mixed traffic flow, which is likely to be more dynamic and volatile, posing serious operational, control, and safety challenges.

    This project addresses this knowledge deficit, and develops an analytical tool with the capability of accurately modelling mixed traffic flow. This new knowledge and model are prerequisites to effective operation and control of traffic flow of traditional, connected, and automated vehicles .

Supervision history

Current supervision

  • Doctor Philosophy

    Dynamic lane-changing behavior modeling framework on urban arterials using deep reinforcement learning

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Fundamental Issues in Calibrating and Validating Microscopic Traffic Dynamics of Automated and Human-driven Vehicles

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Motorized Two-wheeler safety - a comparative risk study of the occupants in Indian and Australian context

    Principal Advisor

  • Doctor Philosophy

    Improving Traffic Dynamics Simulation Quality for Enhanced Safety and Efficiency: Evaluation, Modelling, and Application

    Principal Advisor

    Other advisors: Dr Rocky Chen

  • Doctor Philosophy

    Modelling Driving Behaviour of Mixed Autonomous and Human-Driven Vehicles Flow

    Principal Advisor

    Other advisors: Associate Professor Jiwon Kim

  • Doctor Philosophy

    Crash Data Analytics Based Roadside Risk Modelling Oriented Towards Practical Roadside and Associated Road Geometric Design Using Machine Learning

    Associate Advisor

    Other advisors: Professor Mark Hickman

  • Doctor Philosophy

    Traffic modelling and control in next-generation cities

    Associate Advisor

    Other advisors: Dr Mehmet Yildirimoglu

Completed supervision

Media

Enquiries

Contact Professor Zuduo Zheng directly for media enquiries about:

  • connected and automated vehicles
  • Traffic congestion

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au