Abstract

It is anticipated that Shared Autonomous Vehicles (SAV) may revolutionise the way people travel as it may lead to less ownership of vehicles and a gradual increase in demand responsive mobility. These vehicles are likely to able to park far away from popular destinations after they drop off their clients. It is, therefore, capable of releasing parking spaces around central business districts while cutting down parking search time and cost. But the magnitude at which these spaces will be released in relation to SAV fleet size is not currently known. This work therefore seeks to understand this relationship using the University of the West of England, Frenchay campus characterised by 23 carparks of varying size – as a case study – to quantitatively understand these impacts. This was done by simulating 2181 parking slot within the campus; motor traffic (SAVs and non-SAVs); and the route networks from the 3 entry stations – East, North and Longmead entrances – to each parking slot. Carpark preference data was obtained and analysed. It formed the context on which drivers choose a parking space within the system. These data alongside with the graphical features of the Frenchay campus were imported into ARENA simulation toolkit: a discrete event-based simulation software. Results indicated the obvious that as SAV fleet size increases, spaces released also increases but in addition, individual carpark reacted dynamically in response to the demand on neighbouring carparks. It also showed that there is currently an excess of parking supply compared to the number of vehicles entering the campus daily. It further discusses the potential of multiple occupancy SAVs to further release all parking spaces on the Frenchay campus. The work concludes with the potentials for this research to be extended to a citywide approach with a special interest in the ability for SAV to release kerb parking spaces.

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