Integrating Data and Simulation Towards a Mobility Services Decision-Support System

Abstract

Bike-sharing systems (BSS) have emerged as a new transport service that proliferates in cities worldwide, characterised by their convenience and flexibility. Often confined to central populous areas, their role within the traditional transport network remains ambiguous and the extent of their potential unexplored. My hypothesis is that, based on international examples and data from a Manchester-based BSS in 2017, their operation leads to a biased availability of the service. In consequence, I expect location decisions to directly impact who can use them and thus, lead to transport inequalities. I contend that their inherent flexibility positions them as a valuable means of transport that authorities should make available for a wider population. In consequence, this research endeavors to harness privileged access to BSS data to develop a simulation tool that explores the effects of BSS deployment in Manchester. For this, I propose a data-driven agent-based model (ABM) to simulate various deployment scenarios utilising the former Manchester BSS as a case study. Structured in a three-paper format, the thesis presents a cohesive narrative that unfolds sequentially, highlighting the benefits of coupling New Mobility Services (NMS) data with readily accessible data to inform transport decisions. The first two papers deal with the lack of information about trip purposes and user profiles that are needed to inform the rules and behaviours of the ABM. The third and final paper synthesises the findings from the previous chapters to build an activity-based simulation where agents decide on a series of means of transport to complete daily itineraries. The aim is to understand the effect that BSS availability has on the agents' mobility patterns. The findings from this thesis highlight the importance of accessible transport resources and propose an innovative data-driven approach to look into the operation of BSS.

Date of Award	6 Jan 2025
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Nuno Pinto (Supervisor) & Arkadiusz Wisniowski (Supervisor)