Modelling and analysis of shared autonomous mobility

The anticipated widespread adoption of driverless cars and public service vehicles poses major challenges, both in terms of policymaking and for analysis, forecasting and appraisal. In particular, how might these new technologies affect patterns of individual and collective ownership and use? Will they marginally affect travel patterns and lifestyles, or fundamentally redefine future patterns of mobility? Core to addressing these problems are the tools available for modelling and analysis.

The chapter sets out to review the relevance and reliability of these tools. It first identifies the potential range of passenger vehicle types and service patterns that need to be considered, including interactions between key actors. It draws out the resulting key modelling requirements and associated outputs, including the spatial and temporal dimensions, and documents the uncertainties involved. Key gaps in knowledge about how driverless vehicles will impact our lives are identified, against which the capabilities of our modelling and analytical tools (both with regard to capturing supply and demand responses) are assessed – at generic and practice levels. It assesses the role that agent-based modelling can play and the contribution that unconventional data sources may make. It presents three case study examples of leading-edge modelling applications that begin to address the issues raised, and concludes by outlining remaining challenges.