A Digital Twin framework for behaviourally responsive integrated passenger–freight transport with crowd shipping

Dr Mojtaba Sajadi

Dr Ammar Al-Bazi

Urban transport systems are under growing pressure from population growth, urbanisation,
rising e-commerce demand, and the urgent need for decarbonisation. Expanding physical
infrastructure is often financially and environmentally constrained, making smarter use of
existing systems essential. Integrated passenger–freight transport (IPFT), particularly through
crowdshipping models that use spare passenger capacity to deliver parcels, offers a
promising solution to reduce congestion, emissions, and last-mile vehicle kilometres.
However, the long-term success of IPFT systems depends critically on user trust, behavioural
adaptation, and resilience to disruptions.

This PhD project proposes the development of a Digital Twin (DT) framework for
behaviourally responsive IPFT systems with a specific focus on crowd shipping. While DT
technologies are increasingly used in manufacturing and infrastructure management, their
application in integrated urban mobility systems remains limited especially in incorporating
behavioural dynamics, public trust, and disruption management. The project addresses this
gap by designing a human-centred DT architecture capable of modelling user interaction,
trust formation, and behavioural responses under normal and disrupted conditions.
The research will develop a conceptual DT framework that integrates technical transport
operations with social and behavioural dimensions. Agent-based simulation models will be
constructed to represent interactions between passengers, freight flows, and crowdshipping
platforms. These models will incorporate behavioural data to capture user decision-making
under varying service reliability and disruption scenarios (e.g., delays, extreme weather,
operational failures).

To enhance behavioural realism where empirical data are limited, the project will explore the
use of Large Language Models (LLMs) to generate adaptive user profiles and decision rules.
The DT environment will be integrated with optimisation tools to support scenario analysis
and evaluate operational strategies that balance efficiency, resilience, and user acceptance.
The expected contributions are threefold: (1) a novel behaviourally enriched DT framework
for IPFT systems; (2) simulation-based evidence on how disruptions influence trust and
system performance; and (3) practical guidelines for deploying user-centred DT solutions in
urban mobility planning. By aligning digital innovation with human-centric and sustainability
principles, the project will support more resilient, inclusive, and low-carbon urban transport
systems in the UK and beyond.

International applicants are welcome to apply for this position.

This project covers all tuition fees and includes an annual stipend.

Please note that the successful candidate will be responsible for any costs relating to moving to Birmingham and/or visiting the Aston campus. International students must meet the financial requirements for the visa, flights, and NHS Surcharge. Applicants should be confident that they can meet these costs before applying.

Further information can be found by viewing our Financial Requirements page.

The successful applicant should hold, or expect to achieve:

A First or Upper Second Class Honours undergraduate degree, and a Masters degree with Merit or Distinction, both in relevant subjects.

Qualifications from overseas institutions will be considered, but performance must be equivalent to that described above, and the University reserves the right to ascertain this equivalence according to its own criteria.

Required characteristics

A strong academic background in Industrial Engineering, Operations Research, Computer Science, or a closely related discipline.

Solid knowledge of quantitative modelling, optimisation, and analytical methods

Experience in simulation modelling (agent-based and discrete-event simulation) and Experience with simulation software such as AnyLogic (or similar platforms).

Experience in optimisation tools such as Gurobi, GAMS, or equivalent solvers.

Proficiency in programming languages such as Python and/or C++, with the ability to develop computational models.

Demonstrated research capability, with evidence of prior publications or strong potential to publish in relevant areas.

Strong problem-solving skills and the ability to work independently within an interdisciplinary research environment

Desirable characteristics

Knowledge of transport systems, urban mobility, or integrated passenger–freight transport.

Understanding of Digital Twin technologies or data-driven modelling approaches.

Interest or experience in behavioural modelling, agent-based systems, or human-centred simulation.

Experience working on interdisciplinary projects combining technical and behavioural aspects.

We can only consider applications that are complete and have all supporting documents. Applications that do not provide all the relevant documents will be automatically rejected. Your application must include:

1. English language copies of the transcripts and certificates for all your higher education degrees, including any Bachelor degrees.
2. A Research Statement detailing your understanding of the research area, how you would approach the project, and a brief review of relevant literature. Be sure to use the title of the research project you are applying for. There is no set format or word count.
3. A personal statement which outlines any further information which you think is relevant to your application, such as your personal suitability for research, career aspirations, possible future research interests, and further description of relevant employment experience.
4. A Curriculum Vitae (Resume) which details your education and work history.
5. Two academic referees who can discuss your suitability for independent research. References must be on headed paper, signed and dated no more than 2 years old. At least one reference should be from your most recent University. You can submit your references at a later date if necessary.
6. Evidence that you meet the English Language requirements. If you do not currently meet the language requirements, you can submit this at a later stage.
7. A copy of your passport. Where relevant, include evidence of settled or pre-settled status.

Please contact Dr Mojtaba Sajadi, for more information or for an informal discussion

This position will be based on the Aston Campus in Birmingham, UK. The successful candidate will need to be located within a reasonable distance of the campus, and will be expected to visit in person regularly.

Interviews will be conducted online via Microsoft Teams. If you are shortlisted, you will be contacted directly with details of the interview.

Apply for this position

Alternatively, apply here

If you require further information about the application process, please contact the Postgraduate Admissions team.