Review of Whole System Simulation Methodologies for Assessing Mobility as a Service (MaaS) as an Enabler for Sustainable Urban Mobility

Mobility as a Service (MaaS) is an emerging concept that is being advanced as an effective approach to improve the sustainability of mobility, especially in densely populated urban areas. MaaS can be defined as the integration of various transport modes into a single service, accessible on demand, via a seamless digital planning and payment application. Recent studies have shown the potential reduction in the size of automobile fleets, with corresponding predicted improvements in congestion and environmental impact, that might be realized by the advent of automated vehicles as part of future MaaS systems. However, the limiting assumptions made by these studies point to the difficult challenge of predicting how the complex interactions of user demographics and mode choice, vehicle automation, and governance models will impact sustainable mobility. The work documented in this paper focused on identifying available methodologies for assessing the sustainability impact of potential MaaS implementations from a whole system (STEEP-social, technical, economic, environmental, and political) perspective. In this research, a review was conducted of current simulation tools and models, relative to their ability to support transportation planners, to assess the MaaS concept, holistically, at a city level. The results presented include: a summary of the literature review, a weighted ranking of relevant transportation simulation tools per the assessment criteria, and identification of key gaps in the current state of the art. The gaps include capturing the interaction of demographic changes, mode choice, induced demand, and land use in a single framework that can rapidly explore the impact of alternative MaaS scenarios, on sustainable mobility, for a given city region. These gaps will guide future assessment methodologies for urban mobility systems, and ultimately assist informed decision-making.