
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:
- traffic flow theory, modelling, simulation and optimisation;
- understanding emerging, disruptive, and intelligent mobility technologies’ impact on traffic efficiency, traffic safety, energy consumption, vehicle emissions, etc.;
- developing essential theories, the foundational algorithms and analytics that can seamlessly integrate future mobilities into the existing transportation systems;
- establishing a new breed of control strategies tailored to maximise the power of the connected environment and vehicle automation; and
- 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 a member of the College of Experts, the Australian Research Council, and 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
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Traffic flow theories and operations, with a focus on emerging technologies
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Travel behaviour, strategic transport planning and modeling, and decision making
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Traffic operation and management for big events (e.g., Olympic and Paralympic Games)
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Traffic safety
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Advanced data analysis techniques (e.g., mathematical modeling, econometrics, numerical optimization) in transport engineering
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Research on research (or meta-research)
Works
Search Professor Zuduo Zheng’s works on UQ eSpace
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
2023
Journal Article
Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and Efficiency
Farah, Haneen, Olstam, Johan and Zheng, Zuduo (2023). Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and Efficiency. IEEE Transactions on Intelligent Transportation Systems, 24 (6), 6432-6435. doi: 10.1109/tits.2023.3276596
2023
Journal Article
A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices
Li, Zili, Washington, Simon P., Zheng, Zuduo and Prato, Carlo G. (2023). A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices. Journal of Choice Modelling, 47 100419, 100419. doi: 10.1016/j.jocm.2023.100419
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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, 100013-1. doi: 10.1016/j.commtr.2021.100013
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
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
Funding
Current funding
Past funding
Supervision
Availability
- Professor Zuduo Zheng is:
- Available for supervision
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Available projects
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Fundamental issues in calibrating and validating traffic flow models
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An integrated platform of traffic flow simulation, communication simulation, and driving simulator
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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
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Doctor Philosophy
Fundamental Issues in Calibrating and Validating Microscopic Traffic Dynamics of Automated and Human-driven Vehicles
Principal Advisor
Other advisors: Dr Mehmet Yildirimoglu
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Doctor Philosophy
Autonomous Eco-driving in the Vicinity of Signalized Intersection Using Deep Reinforcement Learning
Principal Advisor
Other advisors: Associate Professor Jiwon Kim
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Doctor Philosophy
Dynamic lane-changing behavior modeling framework on urban arterials using deep reinforcement learning
Principal Advisor
Other advisors: Dr Mehmet Yildirimoglu
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Doctor Philosophy
Motorized Two-wheeler safety - a comparative risk study of the occupants in Indian and Australian context
Principal Advisor
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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
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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
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Doctor Philosophy
Modelling Driving Behaviour of Mixed Autonomous and Human-Driven Vehicles Flow
Principal Advisor
Other advisors: Associate Professor Jiwon Kim
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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
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Doctor Philosophy
Motorized Two-wheeler safety - a comparative risk study of the occupants in Indian and Australian context
Principal Advisor
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Master Philosophy
Synthetic Travel Demand Generation using Data-Driven Methods
Associate Advisor
Other advisors: Honorary Professor Carlo Prato, Associate Professor Jiwon Kim
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Doctor Philosophy
Zonal inference in congestion modelling
Associate Advisor
Other advisors: Honorary Professor Carlo Prato, Associate Professor Jiwon Kim
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Doctor Philosophy
Traffic modelling and control in next-generation cities
Associate Advisor
Other advisors: Dr Mehmet Yildirimoglu
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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
Completed supervision
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2022
Doctor Philosophy
Towards an Autonomous World: Vehicle Users' Preferences Regarding Autonomous Driving
Principal Advisor
Other advisors: Professor Mark Hickman
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2020
Doctor Philosophy
Investigation of lane-changing behaviour in a connected environment
Principal Advisor
Other advisors: Dr Mehmet Yildirimoglu
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2019
Doctor Philosophy
Understanding and Modelling the Car-Following Behaviour of Connected Vehicles
Principal Advisor
Other advisors: Associate Professor Jiwon Kim
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2023
Doctor Philosophy
Demand Management and Estimation in Large-scale Traffic Networks
Associate Advisor
Other advisors: Dr Mehmet Yildirimoglu
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2022
Doctor Philosophy
Public Acceptability of Autonomous Vehicles: Does Contextual Consideration Make a Difference?
Associate Advisor
Other advisors: Honorary Professor Carlo Prato
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2021
Doctor Philosophy
Car Ownership: Modelling the Psychological Aspects of Ownership
Associate Advisor
Other advisors: Honorary Professor Carlo Prato
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2021
Master Philosophy
Estimating Link Flows from Limited Traffic Volume and Sparse Trajectory Data: Generative Modelling Approaches
Associate Advisor
Other advisors: Associate Professor Jiwon Kim
Media
Enquiries
Contact Professor Zuduo Zheng directly for media enquiries about:
- connected and automated vehicles
- Traffic congestion
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