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State the overarching goal/aim of your project.

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Provide an overview of your standing in the field.

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Describe how your project will contribute to solving economic, environmental, social and/or cultural issues

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Introduce the topic and the ‘bigger picture’, using statistics to highlight the significance of research in this field.

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State 3-4 sub-aims of the project

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Discuss how your project will strengthen existing and/or build new international collaborations. Name the investigator, expertise and institution.

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This project will foster international collaboration with Prof Hai Yang at The Hong Kong University of Science and Technology. He is one of the global leading scientists in modelling taxi services. This collaboration will be sustained by research visits  combined with attending the international Hong Kong Society for Transportation Studies (HKSTS) conference.

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Highlight your publication track record, in direct relevance to the proposed research topic. Indicate the esteem in the field.

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The project outcomes will significantly contribute to smart cities initiatives enabling to reduce fuel consumption, noise pollution, greenhouse gas emissions, and personal transport costs leading to safer roads and a better quality of life.

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Outline the strategies you will have in place to disseminate and promote the research outcomes. Be specific about outlets.

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1) To model dynamics of TNC markets (ride-sourcing and ridesharing services)

2) To design and develop control strategies for TNC platforms

3) To design market regulation of competition among shared and automated services.

4) To model and design fully automated TNCs (Automated Taxi - aTaxi)

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Introduce the research questions/knowledge gap that your project will address.

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Include details of the collaborations you have built so far in your research career – both national and international.

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Explain what is innovative about the project, and why. Consider all types of innovation: the concept, methodology, technology, theory.

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Assure the assessors of successful and timely completion of the project, by connecting the proposed activities to your expertise and prior experience, and referring to any preliminary studies.

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This project will generate 9 high-quality research papers in leading ERA-listed journals such as Transportation Research part B and C and IEEE Transactions on ITS. The applicant has established track records in publishing across these top journals.

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Describe in detail the individual steps/stages of your project design, in direct alignment to the project aims.

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Reflect on the qualities at USyd that make it the ideal research environment for your project.

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Analyse the current techniques/models that are used in recent, relevant literature.

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Identify your emerging leadership capabilities

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I have led 3 research groups to deliver industry-funded projects exceeding $160,000 as the lead CI. I am a member of the editorial board of Transportation Research part C (2019-), Transportation Letters (2018-), and Transport Findings (2019-).

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The University of Sydney's program in the domain of Transport Science and Technology is among the largest and most creative transport research groups in Australia; it comprises a distinguished and multidisciplinary team of researchers linked to key areas of transport and is ranked 5th globally by ARWU.

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Clarify your supervisory experience, including as primary or co-supervisor, and highlight the student achievements.

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I have initiated and led fruitful research collaborations with TU Delft [11 in F17], UC Berkeley [17 in F17], U Toronto [9, 11], UQ [27], UNSW, and Monash University [28].

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I am among Australia’s leaders of transport market design and control of shared and automated transport services with a focus on realistic physical modelling of congestion dynamics.

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Summarise the gaps in the current literature which your project will address.

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To summarize, there is a significant gap in the literature to analyse, model, and optimise shared and automated point-to-point transport services based on the non-equilibrium approach.

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I have supervised 2 Postdocs (1 currently is a continuing Research Scientist at CSIRO's Data61, Transport Analytics Group), and have co-supervised 2 PhD students.

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This research project offers an innovative non-equilibrium approach to model, analyse, design, and regulate shared and automated point-to-point services. This novel approach promises more accurate models for operational tasks such as time-varying control of fare and wage by TNCs.

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This project aims to develop quantitative models and market design methods to fundamentally transform the analysis, control, and regulation of shared and automated transport services as a dynamic competitive market to maximise social welfare.

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It is estimated that there are more than 15,000 Uber drivers and one million Uber users in Australia [3]. Reports show that Transport Network Companies (such as Uber) exacerbated traffic conditions in Manhattan from 2013 to 2017, where TNC trips increased 15%, traffic speed deteriorated 15%, and the number of vehicles increased 59%.

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Task 4.1 Decentralised optimisation - Contingency plan of aTaxis (Aim 4).
I will investigate a decentralized cooperative solution for search routing of aTaxi vehicles.

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The project will enrich the academic excellence of shared transport systems domain in Australia and help establish a pioneering research hub at the University of Sydney focused on this topic at the forefront of the transport community.

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Fully justify and detail the methods to be used.

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Explain how the outcomes will contribute to advancing knowledge in the discipline, and the extent to which it will open up new research opportunities.

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How would these transport services be managed and operated? How will the transition from a non-automated non-shared transport service to that end state be achieved? This project answers these challenging research questions.

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Preliminary studies have been performed in [9, 11] that, combined with an initial literature review have identified the challenges of the project. I have delivered externally funded research projects to VicRoads, DATA61, and Austroads as the lead CI. Therefore, it is expected that I will also successfully manage and lead the proposed project and achieve its aims.

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Recent literature reveals a reproducible, unimodal, and low-scatter relationship between time-varying average speed and the average number of vehicles in the network [24]. This parsimonious model, named network Macroscopic Fundamental Diagram (MFD), offers a vast methodological opportunity to quantitatively model and control large-scale networks [26]-[28].

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The proposed search routing method is based on partitioning the network into regions where a homogeneous temporal and spatial distribution of travel requests employing historical data is expected. The partitioning algorithm is essential to guarantee the connectivity of the links in each region.

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My research outputs have attracted substantial recognition with a citation record well-above standards of the field (1288 citations and h-index of 12, Google Scholar, 6/3/2020).