Mapping and Modelling the Sustainability of Dubai’s Transport System

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Prof. Alireza Daneshkhah

Professor of Data Science, Faculty of Mathematics & Data Science Emirates Aviation University Dubai, United Arab Emirates

"As a Professor of Data Science with a long-standing focus on probabilistic modelling, AI, and the analysis of complex engineering and mobility systems, I am deeply motivated by the challenge of transforming rich but fragmented transport data into decisions that shape a more sustainable and resilient urban future. This project offers a unique opportunity to integrate systems thinking, dynamic simulation, and AI-informed analysis to support Dubai’s ambition to lead globally in smart, climate-neutral mobility. I am genuinely excited to drive this work forward, working with our partners to deliver tools and insights that help policymakers understand feedback, anticipate unintended consequences, and design transport strategies that endure."

Mapping and Modelling the Sustainability of Dubai’s Transport System sets out a new paradigm for how cities plan, manage, and future-proof mobility in an era of rapid urban growth, climate imperatives, and technological disruption. Anchored at Emirates Aviation University, an emerging regional leader at the intersection of AI, systems engineering, and urban analytics, the project brings together academic researchers, transport experts, and government partners to build a science-driven, AI-informed decision-support ecosystem for Dubai’s mobility future.

As a global hub for aviation, commerce, and tourism, Dubai faces mounting pressures on its transport system: rising demand, increasing congestion, evolving mobility preferences, and the need to align with net-zero pathways. Current planning tools often rely on siloed datasets or linear forecasts that cannot capture the interdependent feedbacks shaping long-term sustainability. This project transforms that landscape by integrating systems thinking, dynamic simulation, and machine learning into a unified modelling and data platform that supports proactive, evidence-based policy design.

The research programme is organised around five interconnected objectives:

  1. Map and understand: Develop an enhanced systems map capturing behavioural, infrastructural, environmental, and policy feedback loops.
  2. Integrate and govern: Build an interoperable, metadata-rich data repository and web interface for multimodal transport and environmental datasets.
  3. Model and simulate: Create a calibrated system-dynamics model, strengthened with AI-informed parameter estimation, to test intervention scenarios through 2050.
  4. Translate and advise: Produce high-quality policy briefs outlining trade-offs, co-benefits, and adaptive pathways aligned with Dubai’s climate and mobility goals.
  5. Engage and transfer: Deliver structured stakeholder workshops and capacity-building materials to embed tools within institutional workflows.

In collaboration with the University of Hertfordshire (UK) and the RTA, this project will position Dubai as a global reference point for data-intelligent, climate-aligned, and resilient urban mobility, bridging science, policy, and operational practice to deliver measurable societal and environmental impact.

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