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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

21 - 40 of 116 works

2023

Journal Article

Assessing a connected environment's safety impact during mandatory lane-changing: a block maxima approach

Ali, Yasir, Haque, Md. Mazharul and Zheng, Zuduo (2023). Assessing a connected environment's safety impact during mandatory lane-changing: a block maxima approach. IEEE Transactions on Intelligent Transportation Systems, 24 (6), 6639-6649. doi: 10.1109/tits.2022.3147668

Assessing a connected environment's safety impact during mandatory lane-changing: a block maxima approach

2023

Journal Article

Fifth-order A-WENO path-conservative central-upwind scheme for behavioral non-equilibrium traffic models

Chu, Shaoshuai, Kurganov, Alexander, Mohammadian, Saeed and Zheng, Zuduo (2023). Fifth-order A-WENO path-conservative central-upwind scheme for behavioral non-equilibrium traffic models. Communications in Computational Physics, 33 (3), 692-732. doi: 10.4208/cicp.OA-2022-0263

Fifth-order A-WENO path-conservative central-upwind scheme for behavioral non-equilibrium traffic models

2023

Journal Article

Stability evolution of car-following models considering asymmetric driving behavior

Sun, Jie, Zheng, Zuduo and Sun, Jian (2023). Stability evolution of car-following models considering asymmetric driving behavior. Transportation Research Record: Journal of the Transportation Research Board, 2677 (8), 361-371. doi: 10.1177/03611981231156584

Stability evolution of car-following models considering asymmetric driving behavior

2023

Journal Article

Space sharing between pedestrians and micro-mobility vehicles: a systematic review

Zhang, Cheng, Du, Bo, Zheng, Zuduo and Shen, Jun (2023). Space sharing between pedestrians and micro-mobility vehicles: a systematic review. Transportation Research Part D: Transport and Environment, 116 103629, 1-18. doi: 10.1016/j.trd.2023.103629

Space sharing between pedestrians and micro-mobility vehicles: a systematic review

2023

Journal Article

Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach

Zhong, Miner, Kim, Jiwon and Zheng, Zuduo (2023). Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach. IEEE Open Journal of Intelligent Transportation Systems, 4, 14-29. doi: 10.1109/ojits.2022.3233904

Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach

2023

Journal Article

A learning-based discretionary lane-change decision-making model with driving style awareness

Zhang, Yifan, Xu, Qian, Wang, Jianping, Wu, Kui, Zheng, Zuduo and Lu, Kejie (2023). A learning-based discretionary lane-change decision-making model with driving style awareness. IEEE Transactions on Intelligent Transportation Systems, 24 (1), 68-78. doi: 10.1109/tits.2022.3217673

A learning-based discretionary lane-change decision-making model with driving style awareness

2022

Journal Article

A generative car-following model conditioned on driving styles

Zhang, Yifan, Chen, Xinhong, Wang, Jianping, Zheng, Zuduo and Wu, Kui (2022). A generative car-following model conditioned on driving styles. Transportation Research Part C: Emerging Technologies, 145 103926, 1-21. doi: 10.1016/j.trc.2022.103926

A generative car-following model conditioned on driving styles

2022

Journal Article

Corrigendum: “State of data platforms for connected vehicles and infrastructures” (Communications in Transportation Research (2021) 1, (100013), (S2772424721000135), (10.1016/j.commtr.2021.100013))

Lim, Kai Li, Whitehead, Jake, Jia, Dongyao and Zheng, Zuduo (2022). Corrigendum: “State of data platforms for connected vehicles and infrastructures” (Communications in Transportation Research (2021) 1, (100013), (S2772424721000135), (10.1016/j.commtr.2021.100013)). Communications in Transportation Research, 2 100057, 100057. doi: 10.1016/j.commtr.2022.100057

Corrigendum: “State of data platforms for connected vehicles and infrastructures” (Communications in Transportation Research (2021) 1, (100013), (S2772424721000135), (10.1016/j.commtr.2021.100013))

2022

Journal Article

Predicting and explaining lane-changing behaviour using machine learning: a comparative study

Ali, Yasir, Hussain, Fizza, Bliemer, Michiel C. J., Zheng, Zuduo and Haque, Md. Mazharul (2022). Predicting and explaining lane-changing behaviour using machine learning: a comparative study. Transportation Research Part C: Emerging Technologies, 145 103931, 1-20. doi: 10.1016/j.trc.2022.103931

Predicting and explaining lane-changing behaviour using machine learning: a comparative study

2022

Journal Article

A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment

Ali, Yasir, Haque, Md. Mazharul, Zheng, Zuduo and Afghari, Amir Pooyan (2022). A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment. Analytic Methods in Accident Research, 35 100221, 100221. doi: 10.1016/j.amar.2022.100221

A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment

2022

Journal Article

Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aids

Ali, Yasir, Bliemer, Michiel C.J., Haque, Md. Mazharul and Zheng, Zuduo (2022). Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aids. Transportation Research Part C: Emerging Technologies, 136 103531, 103531. doi: 10.1016/j.trc.2021.103531

Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aids

2022

Journal Article

An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environment

Ali, Yasir, Haque, Md Mazharul and Zheng, Zuduo (2022). An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environment. Analytic Methods in Accident Research, 33 100193, 100193. doi: 10.1016/j.amar.2021.100193

An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environment

2022

Journal Article

Processing, assessing, and enhancing the Waymo autonomous vehicle open dataset for driving behavior research

Hu, Xiangwang, Zheng, Zuduo, Chen, Danjue, Zhang, Xi and Sun, Jian (2022). Processing, assessing, and enhancing the Waymo autonomous vehicle open dataset for driving behavior research. Transportation Research Part C: Emerging Technologies, 134 103490, 103490. doi: 10.1016/j.trc.2021.103490

Processing, assessing, and enhancing the Waymo autonomous vehicle open dataset for driving behavior research

2021

Journal Article

A car-following model for connected and automated vehicles with heterogeneous time delays under fixed and switching communication topologies

Li, Yongfu, Chen, Bangjie, Zhao, Hang, Peeta, Srinivas, Hu, Simon, Wang, Yibing and Zheng, Zuduo (2021). A car-following model for connected and automated vehicles with heterogeneous time delays under fixed and switching communication topologies. IEEE Transactions on Intelligent Transportation Systems, 23 (9), 1-13. doi: 10.1109/tits.2021.3134419

A car-following model for connected and automated vehicles with heterogeneous time delays under fixed and switching communication topologies

2021

Journal Article

State of data platforms for connected vehicles and infrastructures

Lim, Kai Li, Whitehead, Jake, Jia, Dongyao and Zheng, Zuduo (2021). State of data platforms for connected vehicles and infrastructures. Communications in Transportation Research, 1 100013, 100013. doi: 10.1016/j.commtr.2021.100013

State of data platforms for connected vehicles and infrastructures

2021

Journal Article

Reasons, challenges, and some tools for doing reproducible transportation research

Zheng, Zuduo (2021). Reasons, challenges, and some tools for doing reproducible transportation research. Communications in Transportation Research, 1 100004, 1-10. doi: 10.1016/j.commtr.2021.100004

Reasons, challenges, and some tools for doing reproducible transportation research

2021

Journal Article

Modelling lane-changing execution behaviour in a connected environment: a grouped random parameters with heterogeneity-in-means approach

Ali, Yasir, Zheng, Zuduo and Haque, Md Mazharul (2021). Modelling lane-changing execution behaviour in a connected environment: a grouped random parameters with heterogeneity-in-means approach. Communications in Transportation Research, 1 100009, 1-14. doi: 10.1016/j.commtr.2021.100009

Modelling lane-changing execution behaviour in a connected environment: a grouped random parameters with heterogeneity-in-means approach

2021

Journal Article

Integrating safety into the fundamental relations of freeway traffic flows: a conflict-based safety assessment framework

Mohammadian, Saeed, Haque, Md. Mazharul, Zheng, Zuduo and Bhaskar, Ashish (2021). Integrating safety into the fundamental relations of freeway traffic flows: a conflict-based safety assessment framework. Analytic Methods in Accident Research, 32 100187, 100187. doi: 10.1016/j.amar.2021.100187

Integrating safety into the fundamental relations of freeway traffic flows: a conflict-based safety assessment framework

2021

Journal Article

Stop or go decisions at the onset of yellow light in a connected environment: a hybrid approach of decision tree and panel mixed logit model

Ali, Yasir, Haque, Md. Mazharul, Zheng, Zuduo and Bliemer, Michiel C.J. (2021). Stop or go decisions at the onset of yellow light in a connected environment: a hybrid approach of decision tree and panel mixed logit model. Analytic Methods in Accident Research, 31 100165, 100165. doi: 10.1016/j.amar.2021.100165

Stop or go decisions at the onset of yellow light in a connected environment: a hybrid approach of decision tree and panel mixed logit model

2021

Journal Article

Examining the driver-pedestrian interaction at pedestrian crossings in the connected environment: A Hazard-based duration modelling approach

Haque, Md. Mazharul, Oviedo-Trespalacios, Oscar, Sharma, Anshuman and Zheng, Zuduo (2021). Examining the driver-pedestrian interaction at pedestrian crossings in the connected environment: A Hazard-based duration modelling approach. Transportation Research Part A: Policy and Practice, 150, 33-48. doi: 10.1016/j.tra.2021.05.014

Examining the driver-pedestrian interaction at pedestrian crossings in the connected environment: A Hazard-based duration modelling approach

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

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

    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

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

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • 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

Need help?

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

communications@uq.edu.au