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Digital Twins’ Application in Intelligent Transport Systems

  • School: School of Science and Technology
  • Study mode(s): Full-time / Part-time
  • Starting: 2023
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded

Overview

NTU's Fully-funded PhD Studentship Scheme 2023

Project ID: S&T32

Intelligent Transport Systems is a new transportation system that aims to resolve a variety of road traffic issues, such as traffic accidents and congestion, by linking people, roads, and vehicles in an information and communications network via cutting-edge technologies. It includes, for example, a road traffic information provision system in which road traffic information is collected via roadside sensors and then provided to drivers.

A Digital Twin (DT) as an emerging field of technology is the integration of a virtual model of an object or system (created to accurately reflect its physical counterpart) with its physical counterpart. As an illustration, the sensors of a wind turbine generate data regarding various aspects of the physical object's performance, including energy output and temperature. This information is then transmitted to a system for processing and applied to the virtual model. The virtual model executes simulations, investigates performance issues, and generates potential enhancements to generate valuable insights, which are then applied to the original physical object. DT has recently garnered attention in the transportation industry. To develop a DT in transportation, the virtual model must be linked to the physical system. In this virtual environment, all road users and their interactions as well as public transport services can be modeled and planned. New measures can be simulated and analyzed before implementing them in real life. DT may serve as a powerful tool for enhancing interoperability between stockholders in a transport system that will be a step towards an intelligent transportation system.

The main goal of the project is to develop a UK-based digital twin for public transportation aiming to manage the employed resources well with less cost and time in a sustainable way.

  • To develop a computational unit that hosts transportation system simulators. The computational unit will connect to the system BIM and real-time data to predict future actions.
  • To select and outfit IoT-based devices for a public transportation system to collect real data from the construction project and to connect the IoT devices to the cloud-based computing unit.
  • To equip the public transportation system with actuators that will depict or execute the actions.
  • To evaluate the applicability of the developed system by running it through diverse operating scenarios.
  • To expand the computational unit by considering a variety of public transportation systems in the United Kingdom.

Supervisory Team:

Reza Vatankhah Barenji, Senior Lecturer in Mechanical Engineering, DoE, (www.sehs.info)

Duo Li, Senior Lecturer in Engineering, DoE

Entry qualifications

For the eligibility criteria, visit our studentship application page.

How to apply

To make an application, please visit our studentship application page.

Fees and funding

This is part of NTU's 2023 fully-funded PhD Studentship Scheme.

Guidance and support

Application guidance can be found on our studentship application page.

Still need help?

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