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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, and a former DECRA Research Fellow sponsored by 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 is currently listed as the Top 2% of Scientists in Logistics and Transportation by Scopus & Stanford University. 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

116 works between 2006 and 2024

61 - 80 of 116 works

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

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

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

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 game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment

Ali, Yasir, Zheng, Zuduo, Haque, Md. Mazharul and Wang, Meng (2019). A game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment. Transportation Research Part C: Emerging Technologies, 106, 220-242. doi: 10.1016/j.trc.2019.07.011

A game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment

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

2019

Journal Article

Modelling car-following behaviour of connected vehicles with a focus on driver compliance

Sharma, Anshuman, Zheng, Zuduo, Bhaskar, Ashish and Haque, Md. Mazharul (2019). Modelling car-following behaviour of connected vehicles with a focus on driver compliance. Transportation Research Part B: Methodological, 126, 256-279. doi: 10.1016/j.trb.2019.06.008

Modelling car-following behaviour of connected vehicles with a focus on driver compliance

2019

Journal Article

Estimating and comparing response times in traditional and connected environments

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Md. Mazharul (2019). Estimating and comparing response times in traditional and connected environments. Transportation Research Record, 2673 (4), 036119811983796-684. doi: 10.1177/0361198119837964

Estimating and comparing response times in traditional and connected environments

2019

Journal Article

Is more always better? The impact of vehicular trajectory completeness on car-following model calibration and validation

Sharma, Anshuman, Zheng, Zuduo and Bhaskar, Ashish (2019). Is more always better? The impact of vehicular trajectory completeness on car-following model calibration and validation. Transportation Research Part B: Methodological, 120, 49-75. doi: 10.1016/j.trb.2018.12.016

Is more always better? The impact of vehicular trajectory completeness on car-following model calibration and validation

2019

Journal Article

Short-term traffic flow forecasting: a component-wise gradient boosting approach with hierarchical reconciliation

Li, Zili, Zheng, Zuduo and Washington, Simon (2019). Short-term traffic flow forecasting: a component-wise gradient boosting approach with hierarchical reconciliation. IEEE Transactions on Intelligent Transportation Systems, 21 (12) 8883246, 1-13. doi: 10.1109/tits.2019.2948381

Short-term traffic flow forecasting: a component-wise gradient boosting approach with hierarchical reconciliation

2018

Journal Article

A pattern recognition algorithm for assessing trajectory completeness

Sharma, Anshuman, Zheng, Zuduo and Bhaskar, Ashish (2018). A pattern recognition algorithm for assessing trajectory completeness. Transportation Research Part C: Emerging Technologies, 96, 432-457. doi: 10.1016/j.trc.2018.09.027

A pattern recognition algorithm for assessing trajectory completeness

2018

Journal Article

Connectivity's impact on mandatory lane-changing behaviour: evidences from a driving simulator study

Ali, Yasir, Zheng, Zuduo and Haque, Md. Mazharul (2018). Connectivity's impact on mandatory lane-changing behaviour: evidences from a driving simulator study. Transportation Research Part C: Emerging Technologies, 93, 292-309. doi: 10.1016/j.trc.2018.06.008

Connectivity's impact on mandatory lane-changing behaviour: evidences from a driving simulator study

2018

Journal Article

Thinking together about the future when you are not together: the effectiveness of using developed scenarios among geographically distributed groups

Hew, Aiwen, Perrons, Robert K., Washington, Simon, Page, Lionel and Zheng, Zudou (2018). Thinking together about the future when you are not together: the effectiveness of using developed scenarios among geographically distributed groups. Technological Forecasting and Social Change, 133, 206-219. doi: 10.1016/j.techfore.2018.04.005

Thinking together about the future when you are not together: the effectiveness of using developed scenarios among geographically distributed groups

2018

Journal Article

User satisfaction with train fares: a comparative analysis in five Australian cities

Paramita, Puteri, Zheng, Zuduo, Haque, Md Mazharul, Washington, Simon and Hyland, Paul (2018). User satisfaction with train fares: a comparative analysis in five Australian cities. PLoS One, 13 (6) e0199449, e0199449. doi: 10.1371/journal.pone.0199449

User satisfaction with train fares: a comparative analysis in five Australian cities

2018

Journal Article

Modeling and predicting stochastic merging behaviors at freeway on-ramp bottlenecks

Sun, Jian, Zuo, Kang, Jiang, Shun and Zheng, Zuduo (2018). Modeling and predicting stochastic merging behaviors at freeway on-ramp bottlenecks. Journal of Advanced Transportation, 2018 9308580, 1-15. doi: 10.1155/2018/9308580

Modeling and predicting stochastic merging behaviors at freeway on-ramp bottlenecks

2018

Journal Article

Stability analysis methods and their application to car-following models in conventional and connected environments

Sun, Jie, Zheng, Zuduo and Sun, Jian (2018). Stability analysis methods and their application to car-following models in conventional and connected environments. Transportation Research Part B: Methodological, 109 (2018), 212-237. doi: 10.1016/j.trb.2018.01.013

Stability analysis methods and their application to car-following models in conventional and connected environments

2017

Journal Article

Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level

Saifuzzaman, Mohammad, Zheng, Zuduo, Haque, Md. Mazharul and Washington, Simon (2017). Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level. Transportation Research Part B: Methodological, 105, 523-538. doi: 10.1016/j.trb.2017.09.023

Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level

2017

Journal Article

Projected prevalence of car-sharing in four Asian-Pacific countries in 2030: what the experts think

Zhou, Fan, Zheng, Zuduo, Whitehead, Jake, Perrons, Robert, Page, Lionel and Washington, Simon (2017). Projected prevalence of car-sharing in four Asian-Pacific countries in 2030: what the experts think. Transportation Research Part C: Emerging Technologies, 84, 158-177. doi: 10.1016/j.trc.2017.08.023

Projected prevalence of car-sharing in four Asian-Pacific countries in 2030: what the experts think

2017

Conference Publication

Investigating household level trip sharing: A case study of future car sharing and autonomous vehicle adopters in Australia

Aminmansour, Sadaf, Prato, Carlo G., Washington, Simon P. and Zheng, Zuduo (2017). Investigating household level trip sharing: A case study of future car sharing and autonomous vehicle adopters in Australia. 39th Australasian Transport Research Forum, ATRF 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, Australia: ATRF, Commonwealth of Australia.

Investigating household level trip sharing: A case study of future car sharing and autonomous vehicle adopters in Australia

Funding

Current funding

  • 2024 - 2026
    Safe and efficient eco-driving using connected and automated vehicles
    ARC Discovery Projects
    Open grant
  • 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
  • 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 - 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

Past funding

  • 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
  • 2021 - 2023
    Urban Freight Shifts
    iMove Cooperative Research Centre
    Open grant
  • 2020 - 2023
    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

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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

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

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

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

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Quantitative Coupling Relationship between Safety and Efficiency of Mixed Traffic Flow with Connected and Automated vehicles and Human-driven vehicles

    Principal Advisor

    Other advisors: Dr Rocky Chen

  • Doctor Philosophy

    Operation Strategy of Shared Autonomous Vehicles with Various Passenger Capacity on the Basis of Ridesharing

    Principal Advisor

    Other advisors: Associate Professor Jiwon Kim

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    Zonal inference in congestion modelling

    Associate Advisor

    Other advisors: Honorary Professor Carlo Prato, Associate Professor Jiwon Kim

  • 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

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