Probing the Performance of the Edinburgh Bike Sharing System using SSTL

Kreikemeyer, Justin N. and Hillston, Jane and Uhrmacher, Adelinde M. (2020) Probing the Performance of the Edinburgh Bike Sharing System using SSTL. In: ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS 2020), 15-17 Jun 2020, Miami, Florida, USA. Proceedings, published by ACM, New York, USA, pp. 141-152.

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Bike sharing systems are a popular form of sustainable and affordable transport that has been introduced to cities around the world in recent years. Nevertheless, designing these systems to meet the requirements of the operators and also satisfy the demand of the users, is a complex problem. In this paper we focus on the recently introduced bike sharing system in the city of Edinburgh and use data analytics combined with formal modelling approaches to investigate the current behaviour and possible future behaviour of the system. Specifically we use a spatio-temporal logic, SSTL (the signal spatio-temporal logic), to formally characterise properties of the captured system, and through this identify potential problems as user demand grows. In order to investigate these problems further we use the CARMA modelling language and tool suite to construct a stochastic model of the system to investigate possible future scenarios, including decentralised redistribution. This model is parameterised and validated using data from the operational system.

Item Type: Conference or Workshop Item (Paper)
Additional Information: (to appear)
Projects: ESCeMMo, MoSiLLDe