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Sustainable Intelligent Transport Systems with Digital Twins

  • School: School of Science and Technology
  • Starting: 2023
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded


Project ID: SST8

Despite the potential benefits of Intelligent Transport Systems (ITS) in addressing traffic issues, there is a need for more sustainable solutions that take into account the environmental impact and resource management of these systems. Furthermore, traditional approaches to transportation planning and management may not effectively consider the complexity of interactions between different stakeholders and transportation modes. Therefore, there is a pressing need for the development of Digital Twins that can enhance interoperability and optimize the performance of transportation systems while minimizing their environmental impact and resource usage.

ITSs have the potential to revolutionize transportation by utilizing cutting-edge technologies to address traffic issues such as congestion and accidents. However, to ensure the long-term sustainability of these systems, it is important to consider their environmental impact and resource management. Therefore, the proposed project aims to develop sustainable UK-based Digital Twins for a transportation system that effectively manages resources with less cost and time.

The Digital Twins integrates a virtual model of the transportation system with its physical counterpart, allowing for real-time monitoring, analysis, and simulation. This technology can help enhance interoperability between stakeholders in a transport system and optimize its performance in a sustainable manner. By connecting IoT devices to a cloud-based computing unit, real data can be collected from the construction project, enabling the system to predict future actions and simulate various operating scenarios.

The specific goals of the project are as follows:

  • Develop a computational unit that hosts transportation system simulators and connects to the system's real-time data to predict future actions.
  • Select and outfit IoT-based devices for the transportation system to collect real data and connect them to the cloud-based computing unit.
  • Equip the transportation system with actuators that depict or execute the actions.
  • Evaluate the applicability of the developed system by running it through diverse operating scenarios.
  • Expand the computational unit to consider a variety of transportation systems in the United Kingdom.

Supervisory Team:

Reza Vatankhah Barenji

Duo Li

Entry qualifications

  • 1st class / 2:1 undergraduate degree, and / or equivalent
  • Completed masters level qualification and / or evidence of substantive published research works

How to apply

Please visit our how to apply page for a step-by-step guide and make an application and include the project ID in your application

Application deadline: Thursday 8 June 2023.

Interviews will take place in mid-June 2023

Fees and funding

This is an NTU Studentship funded opportunity.

Guidance and support

Find out about guidance and support for PhD students.

Still need help?

Duo Li