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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

61 - 80 of 130 works

2021

Journal Article

Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Mazharul Haque, Md. (2021). Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors. Transportation Research Part C: Emerging Technologies, 124 102934, 1-21. doi: 10.1016/j.trc.2020.102934

Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors

2021

Journal Article

Integrated simulation platform for conventional, connected and automated driving: a design from cyber–physical systems perspective

Jia, Dongyao, Sun, Jie, Sharma, Anshuman, Zheng, Zuduo and Liu, Bingyi (2021). Integrated simulation platform for conventional, connected and automated driving: a design from cyber–physical systems perspective. Transportation Research Part C: Emerging Technologies, 124 102984, 1-19. doi: 10.1016/j.trc.2021.102984

Integrated simulation platform for conventional, connected and automated driving: a design from cyber–physical systems perspective

2021

Book Chapter

Connected and automated vehicles: opportunities and challenges for transportation systems, smart cities, and societies

Sharma, Anshuman and Zheng, Zuduo (2021). Connected and automated vehicles: opportunities and challenges for transportation systems, smart cities, and societies. Automating cities: design, construction, operation and future impact. (pp. 273-296) edited by Brydon T. Wang and C. M. Wang. Singapore: Springer. doi: 10.1007/978-981-15-8670-5_11

Connected and automated vehicles: opportunities and challenges for transportation systems, smart cities, and societies

2021

Journal Article

An enhanced predictive cruise control system design with data-driven traffic prediction

Jia, Dongyao, Chen, Haibo, Zheng, Zuduo, Watling, David, Connors, Richard, Gao, Jianbing and Li, Ying (2021). An enhanced predictive cruise control system design with data-driven traffic prediction. IEEE Transactions on Intelligent Transportation Systems, 23 (7), 1-14. doi: 10.1109/tits.2021.3076494

An enhanced predictive cruise control system design with data-driven traffic prediction

2021

Journal Article

A dynamic sensitivity model for unidirectional pedestrian flow with overtaking behaviour and its application on social distancing's impact during COVID-19

Du, Bo, Zhang, Cheng, Shen, Jun and Zheng, Zuduo (2021). A dynamic sensitivity model for unidirectional pedestrian flow with overtaking behaviour and its application on social distancing's impact during COVID-19. IEEE Transactions on Intelligent Transportation Systems, 23 (8), 1-14. doi: 10.1109/TITS.2021.3093714

A dynamic sensitivity model for unidirectional pedestrian flow with overtaking behaviour and its application on social distancing's impact during COVID-19

2020

Journal Article

Detecting, analysing, and modelling failed lane-changing attempts in traditional and connected environments

Ali, Yasir, Zheng, Zuduo, Mazharul Haque, Md., Yildirimoglu, Mehmet and Washington, Simon (2020). Detecting, analysing, and modelling failed lane-changing attempts in traditional and connected environments. Analytic Methods in Accident Research, 28 100138, 100138. doi: 10.1016/j.amar.2020.100138

Detecting, analysing, and modelling failed lane-changing attempts in traditional and connected environments

2020

Journal Article

Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres

Ali, Yasir, Bliemer, Michiel C. J., Zheng, Zuduo and Haque, Md. Mazharul (2020). Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres. Transportation Research Part C: Emerging Technologies, 121 102871, 1-21. doi: 10.1016/j.trc.2020.102871

Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres

2020

Journal Article

The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller

Sun, Jie, Zheng, Zuduo and Sun, Jian (2020). The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller. Transportation Research Part B: Methodological, 142, 58-83. doi: 10.1016/j.trb.2020.10.004

The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller

2020

Journal Article

Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment

Ali, Yasir, Bliemer, Michiel C.J., Zheng, Zuduo and Haque, Md. Mazharul (2020). Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment. Transportation Research Part C: Emerging Technologies, 120 102816, 102816. doi: 10.1016/j.trc.2020.102816

Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment

2020

Journal Article

Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Mazharul (2020). Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations. Analytic Methods in Accident Research, 27 100127, 100127. doi: 10.1016/j.amar.2020.100127

Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations

2020

Journal Article

The impact of the connected environment on driving behavior and safety: a driving simulator study

Ali, Yasir, Sharma, Anshuman, Haque, Md. Mazharul, Zheng, Zuduo and Saifuzzaman, Mohammad (2020). The impact of the connected environment on driving behavior and safety: a driving simulator study. Accident Analysis and Prevention, 144 105643, 105643. doi: 10.1016/j.aap.2020.105643

The impact of the connected environment on driving behavior and safety: a driving simulator study

2020

Journal Article

Examining the impact of car-sharing on private vehicle ownership

Zhou, Fan, Zheng, Zuduo, Whitehead, Jake, Perrons, Robert K., Washington, Simon and Page, Lionel (2020). Examining the impact of car-sharing on private vehicle ownership. Transportation Research Part A: Policy and Practice, 138, 322-341. doi: 10.1016/j.tra.2020.06.003

Examining the impact of car-sharing on private vehicle ownership

2020

Journal Article

Investigating the long- and short-term driving characteristics and incorporating them into car-following models

Chen, Xiaoyun, Sun, Jian, Ma, Zian, Sun, Jie and Zheng, Zuduo (2020). Investigating the long- and short-term driving characteristics and incorporating them into car-following models. Transportation Research Part C: Emerging Technologies, 117 102698, 102698. doi: 10.1016/j.trc.2020.102698

Investigating the long- and short-term driving characteristics and incorporating them into car-following models

2020

Journal Article

Exploring the spatial-temporal relationship between rainfall and traffic flow: a case study of Brisbane, Australia

Qi, Yanmin, Zheng, Zuduo and Jia, Dongyao (2020). Exploring the spatial-temporal relationship between rainfall and traffic flow: a case study of Brisbane, Australia. Sustainability, 12 (14) 5596, 5596. doi: 10.3390/su12145596

Exploring the spatial-temporal relationship between rainfall and traffic flow: a case study of Brisbane, Australia

2020

Journal Article

Using digital technologies to deliver scenarios to geographically dispersed stakeholders: lessons learned from the transportation sector

Hew, Aiwen, Perrons, Robert K., Washington, Simon, Page, Lionel and Zheng, Zuduo (2020). Using digital technologies to deliver scenarios to geographically dispersed stakeholders: lessons learned from the transportation sector. Futures, 120 102567, 102567. doi: 10.1016/j.futures.2020.102567

Using digital technologies to deliver scenarios to geographically dispersed stakeholders: lessons learned from the transportation sector

2020

Journal Article

Understanding the discretionary lane-changing behaviour in the connected environment

Ali, Yasir, Zheng, Zuduo, Mazharul Haque, Md., Yildirimoglu, Mehmet and Washington, Simon (2020). Understanding the discretionary lane-changing behaviour in the connected environment. Accident Analysis and Prevention, 137 105463, 1-18. doi: 10.1016/j.aap.2020.105463

Understanding the discretionary lane-changing behaviour in the connected environment

2020

Journal Article

Microscopic modelling of area-based heterogeneous traffic flow: area selection and vehicle movement

Sarkar, Nikhil Chandra, Bhaskar, Ashish, Zheng, Zuduo and Miska, Marc P (2020). Microscopic modelling of area-based heterogeneous traffic flow: area selection and vehicle movement. Transportation Research Part C: Emerging Technologies, 111, 373-396. doi: 10.1016/j.trc.2019.12.013

Microscopic modelling of area-based heterogeneous traffic flow: area selection and vehicle movement

2020

Journal Article

Preference heterogeneity in mode choice for car-sharing and shared automated vehicles

Zhou, Fan, Zheng, Zuduo, Whitehead, Jake, Washington, Simon, Perrons, Robert K. and Page, Lionel (2020). Preference heterogeneity in mode choice for car-sharing and shared automated vehicles. Transportation Research Part A: Policy and Practice, 132, 633-650. doi: 10.1016/j.tra.2019.12.004

Preference heterogeneity in mode choice for car-sharing and shared automated vehicles

2019

Journal Article

Long-term forecasts for energy commodities price: what the experts think

Zhou, Fan, Page, Lionel, Perrons, Robert K., Zheng, Zuduo and Washington, Simon (2019). Long-term forecasts for energy commodities price: what the experts think. Energy Economics, 84 104484, 104484. doi: 10.1016/j.eneco.2019.104484

Long-term forecasts for energy commodities price: what the experts think

2019

Journal Article

A hazard-based duration model to quantify the impact of connected driving environment on safety during mandatory lane-changing

Ali, Yasir, Haque, Md. Mazharul, Zheng, Zuduo, Washington, Simon and Yildirimoglu, Mehmet (2019). A hazard-based duration model to quantify the impact of connected driving environment on safety during mandatory lane-changing. Transportation Research Part C: Emerging Technologies, 106, 113-131. doi: 10.1016/j.trc.2019.07.015

A hazard-based duration model to quantify the impact of connected driving environment on safety during mandatory lane-changing

Funding

Current funding

  • 2026 - 2029
    Shaping net-zero cities with safe and efficient micromobility solutions
    ARC Discovery Projects
    Open grant
  • 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

Looking for a supervisor? Read our advice on how to choose 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

    SEEN ¿ A Sustainable Energy-Efficient Novel Driver Behaviour Model for the Future of Transport: Development, Assessment, and Application

    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