Transport model
This is where demand and supply finally meet.
In one sentence
Transport models are abstract and simplified representations of the transport sector, covering both demand and supply, that define its characteristics and structure in order to understand its current situation or test future developments (Bandini, Manzoni and Vizzari, 2009; Alvarez Castro, 2024).
The handbook describes three main families of model. They are not simply alternatives; each was developed to address a limitation of the one before it.
The four-step model (FSM)
The most well-known travel demand model is the so-called four-step model (FSM).
| Originally from | The 1960s |
| Used for | Forecasting, understanding and assessing future demand and performance of a transportation system |
| Typical scale | Regional or sub-regional (McNally, 2007) |
It remains the primary tool for this kind of assessment, and its four stages, introduced in the transport demand chapter, are still the vocabulary most transport planning is conducted in.
Activity-based models (AcBMs)
Activity-based models analyse travel as daily or multi-day patterns of behaviour, related to and derived from differences in lifestyles and activity participation among the population (McNally, 2000).
The shift they represent is fundamental:
| From | To |
|---|---|
| Computations on zonal aggregates | Decision making of individuals (Horni, 2013; Ziemke, 2023) |
This also enables something the four-step model cannot do: the analysis of policy impacts on certain subgroups of the population, grouped by similar socio-demographic characteristics (Kitamura, 1988; Ziemke, 2023).
Why subgroup analysis matters here
An aggregate model can report that a policy saves ten thousand vehicle-hours. Only an individual-level model can say whether those savings accrue to people who were already well served.
Since the IMP assesses social and equity impacts, this capability is a requirement rather than a refinement.
Agent-based models (AgBMs)
A more sophisticated branch of modelling is the use of transport agent-based models.
Agent-based methods simulate travel-related decisions at the level of individual agents and represent their interactions with other agents and the wider transport system (Department for Transport, 2024b).
This type of model enhances activity-based models because the spatio-temporal interactions between agents and the environment are taken into account. The result is a microscopic representation of agents' travel decisions, revealing their behaviours and the implications of their interaction in the transportation system (Kagho et al., 2020).
The distinction between AcBM and AgBM
Both represent individuals. The difference is interaction.
An activity-based model can describe what each person plans to do. An agent-based model additionally simulates what happens when they all try to do it at once, on a network with finite capacity, and lets congestion emerge from that rather than assuming it.
For disruption analysis this is decisive: the effect of a closed road is largely a story about everyone rerouting into everyone else.
How the three compare
| Four-step | Activity-based | Agent-based | |
|---|---|---|---|
| Unit of analysis | Zonal aggregates | Individuals | Individuals |
| Represents interaction | No | No | Yes |
| Congestion | Assigned | Assigned | Emerges |
| Subgroup impacts | Limited | Yes | Yes |
What this chapter covers
| Page | What you will find |
|---|---|
| MATSim | The framework and its iterative co-evolutionary loop |
| Configuration | The config file and the minimum a scenario needs |
| Inputs | Demand, supply and configuration files |
| Outputs | The events file and what can be derived from it |
| MATRA | The specialised freight and electrification model |
| Further reading | Documentation, guidance and references |