Co-simulation of traffic and system dynamics models for long-term transport policy impact assessment

Overview

Transport policies often produce effects across multiple time scales. For example, a policy may have an immediate effect on congestion and travel time, while also influencing longer-term changes in travel demand, accessibility, land value, and origin–destination travel patterns. However, detailed traffic simulation models usually focus on short-term vehicle movements, while strategic policy models often represent long-term feedback loops at a more aggregate level.

This project will investigate how microscopic traffic simulation and system dynamics modelling can be coupled to support long-term transport policy assessment. The project is interdisciplinary, combining transport engineering, traffic simulation, systems thinking, policy evaluation, and computational modelling.

Research engagement

This is an exploratory research project that combines literature review, conceptual modelling, and prototype development. The project will focus on understanding how short-term traffic simulation outputs can be linked with longer-term feedback models, such as system dynamics models.

The student will engage with:

• Literature on traffic simulation, system dynamics, transport policy modelling, and co-simulation.
• Open-source microscopic traffic simulation using existing tools like SUMO.
• System dynamics modelling concepts and tools.
• A simplified case study prototyping both traffic simulation and system dynamic in a co-simulation.
• Critical reflection on the strengths, limitations, and future research potential of this modelling approach.

Research activities

The main activities are:

• Conduct a focused literature review on co-simulation between traffic simulation and system dynamics models.
• Identify examples where short-term transport performance and long-term policy feedback loops are modelled together.
• Review possible architectures for linking SUMO with a system dynamics simulator or a Python-based system dynamics model.
• Develop a simple conceptual framework showing how information could be exchanged between the two modelling environments.
• Build an initial proof-of-concept simulation in which outputs from SUMO, such as travel time or congestion, influence a simple long-term feedback model.
• Document the modelling assumptions, technical challenges, limitations, and possible future extensions.

Research skills

Through this project, you will gain experience in:

• Conducting and synthesising a focused academic literature review.
• Understanding the role of traffic simulation in transport engineering and planning.
• Using or learning SUMO for microscopic traffic simulation.
• Applying system dynamics concepts to transport policy problems.
• Developing simple modelling workflows using Python or related tools.
• Communicating modelling assumptions, limitations, and research findings.
• Identifying future research questions from an exploratory modelling study.

Outcomes

The expected outcomes of the project are:

• A structured literature review on co-simulation approaches linking traffic simulation and system dynamics.
• A conceptual framework for coupling microscopic traffic simulation with long-term transport policy feedback models.
• A small proof-of-concept prototype linking SUMO with a system dynamics model or Python-based equivalent.
• A short research report summarising the methodology, findings, limitations, and future research opportunities.

Skills and experience

This project would suit a student interested in transport engineering, traffic simulation, transport planning, urban systems, policy evaluation, or computational modelling.

The ideal student would have an interest in one or more of the following areas:

• Transport modelling or transport planning.
• Traffic simulation.
• System dynamics or systems thinking.
• Python programming.

Prior experience with SUMO, system dynamics software would be beneficial but is not essential. Prior experience with Python is recommended.

Start date

2 November, 2026

End date

19 February, 2027

Location

GP Campus

Contact

Sebastien Glaser

3138 4911

sebastien.glaser@qut.edu.au