Probing the Performance of the Edinburgh Bike Sharing System using SSTL

Justin N. Kreikemeyer; Jane Hillston; Adelinde Uhrmacher

doi:10.1145/3384441.3395990

Probing the Performance of the Edinburgh Bike Sharing System using SSTL

Started Jan 1, 0001; Published Jun 15, 2020; Last updated Jul 5, 2026; research

Abstract

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.

2020

Probing the Performance of the Edinburgh Bike Sharing System using SSTL.
Justin N. Kreikemeyer, Jane Hillston, Adelinde Uhrmacher. In Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM PADS '20), June 15-17, Miami, FL, USA. ACM, New York, NY, USA, 141-152.
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