New forms of mobility reshape the transportation landscape, changing movement for both their users and others in the environment. The transition period during which novel forms of travel are being explored can be a challenging time while the use of spaces must be renegotiated. E-scooters, which have recently been more widely introduced to the UK, are experiencing such a moment as riders, planners, and other users of the streetscape are determining what role this technology will play in communities. The data gaps surrounding e-scooters can make this an especially difficult question for planners because of the cost of gathering relevant observational data, much of which is held under private company ownership. In light of this, this work presents an agent-based model developed to examine the integration of e-scooters into existing streetscapes. Agent-based models explore phenomena through focusing on individual behaviour and rules which in turn gives rise to emergent large scale patterns. These patterns can be dissected and interrogated with a variety of tools, allowing us to tease out individual as well as group experiences of different scenarios. An agent-based approach allows us to capture the individual behaviours of e-scooter users and those of cyclists, drivers of variously sized vehicles, pedestrians, and others present in the environment. By focusing on the interactions of these various street users, we can explore how different approaches to e-scooter integration may fare relative to varying street configurations. Their decision frameworks are informed by observational studies of e-scooter users in order to augment the available data. We discuss the current state of understanding e-scooter behaviour and the potential modelling applications, present an initial behavioural framework of e-scooter decision making and inter-modal interactions, and highlight some preliminary results examining the differences between e-scooters operating on roads versus shared segregated cycle lanes. The work concludes with a case study comparing two modelled scenarios, one including a segregated cycle lane and one without. Drawing upon metrics such as the route segmentation/ cut-off rate and average travel comfort, we can more precisely explore how new forms of mobility will influence different kinds of street users in order to better understand the trade-offs associated with different paths forward.
Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model
