Cities worldwide experience growing traffic volumes, leading to problems such as congestion, diminished accessibility, bad air quality and high greenhouse gas emissions. The typical response to these issues in transport planning is some combination of extending capacity (e.g. through road construction or shorter train intervals), facilitating or enforcing shifts to more efficient modes (e.g. from private cars to public transport) or imposing access restrictions to bring down motor traffic volumes (e.g. road pricing or parking management).

However, from a systems-oriented perspective, traffic volumes are the result of people’s strategic location choices, given specific characteristics of housing, workplaces and the available means of transport connecting them. In this view, people will choose a home that maximises accessibility without exceeding their monetary and time budgets, thereby shaping the development of housing and transport infrastructure with their decisions. Speeding up traffic flow in such a system will eventually lead to greater travelled distances and higher overall traffic volumes, as this makes it possible to connect remote economical housing with high-paying jobs in city centres within acceptable commute times.

As transport and land use systems exert mutual influence on each other, a series of land use and transport interaction (LUTI) models have been created which take these influences into account. They deliver useful forecasts based on projected changes in their inputs, like level of income, land availability and demographic development (Wegener, 2016).

One model constraint, where usually no change is assumed, is the time used for mobility or travel time budget. As a person’s total time budget is naturally limited to 24 hours per day and the proportion of time being used for mobility was found to be nearly constant in many aggregate studies, a constant travel time budget is assumed (Stopher, Ahmed, & Liu, 2017). However, the clear separation between time used for mobility, work or leisure can no longer be maintained with the diffusion of ICTs which enable the use of an increasing amount of time in transit for both work and leisure activities.

Whilst today the opportunities for full-fledged secondary activities are limited mainly to public transport services, the advent of autonomous vehicles (AVs) will free up driving time to be used in similar ways. Even though details about the AV rollout and their level of service remain unclear, the influence on the valuation of travel time and their respective consequences for traffic volume, land use changes, and total energy consumption in different scenarios can be modelled.

Therefore, the aim of the dissertation will be to compare the modelled scenarios with the help of a set of sustainability indicators and identify leverage for policy and practicable pathways for the necessary transition to a sustainable mobility system.


  • Building a System Dynamics model of the valuation of time in different transport modes and connect it to the MARS land-use and transportation interaction model
  • Developing scenarios for the rollout of autonomous vehicles and assessing them based on various indicators for sustainable mobility
  • Identifying leverage for policy and practicable pathways for the transition to a sustainable mobility system


Stopher, P. R., Ahmed, A., & Liu, W. (2017). Travel time budgets: new evidence from multi-year, multi-day data. Transportation, 44(5), 1069–1082.

Wegener, M. (2016). Overview of Land Use Transport Models. In D. A. Hensher & K. Button (Eds.), Transport Geography and Spatial Systems. Handbook 5 of the Handbook in Transport. (pp. 127–146). Kidlington: Pergamon/Elsevier Science.