Four academic feasibility studies that were jointly awarded funding in an RSSB competition on ‘Data to Improve Customer Experience’, which was run in association with RDG and through RRUKA, have announced their findings.
Two projects – one led by Manchester Metropolitan University and the other by the University of Surrey – looked at novel applications for providing customer information. A project by the University of Kent explored the use of predictive models for crowding on trains, and another by the University of Southampton investigated ways of using passenger loading data to influence behaviour.
These projects have contributed to improving industry’s understanding of passenger needs, investigating practical ways to use existing data streams to improve the customer experience. Transforming this understanding into tangible benefits for the rail industry and its customers is the next challenge. RSSB, RRUKA and RDG are working together to bring representatives from across the industry together to progress these projects and unlock the true potential of data.
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More information on the projects is available below and on SPARK.
“Shortly arriving at…” Development of an innovative framework for customer-centric rail passenger information applications
This project sought to enable a transformation of the customer experience through information that is context-centric rather than data-centric. The project was led by academic experts in ‘ontologies’ – a new approach in computer science – at the core of this research, and was supported by experienced digital developers. The project also involved industry experts from Abellio and Transport for Greater Manchester.
The intention is to enable the foundations of an entirely new approach to building software applications that support customer needs rather than being driven by available data.
Integrating data sources to enhance the experience for passengers with special needs and/or disabilities through privacy aware mobile applications
The project brought together a range of expertise – including computer science, security and tourism specialists (University of Surrey), transport specialists (University of Southampton) and user-centred design experts (Loughborough University) – to investigate how existing and new rail data sources can be used to enhance the passenger experience and provide assistance to passengers with special needs and/or disabilities, for example those with limited mobility or vision impairment, particularly when unplanned disruption occurs. Technical prototypes were created, demonstrating how relevant transport data can be integrated to meet the needs of customers, how the location of passengers can be determined and used to provide benefit to them, and how security and privacy of personal data can be maintained.
Development of Intelligent Predictive Models for Crowding on Trains using Data-driven Methodologies
The project developed accurate and practical prediction models for rail crowing using an intelligent data-driven modelling method. These models can be merged into the existing software tools to provide customers with detailed crowd prediction information before they and support better decision-making.
Use of passenger loading data to influence behaviour and provide an improved experience for passengers and operators alike
This project sought to prove that it is feasible to mitigate crowding by improving information provision and influencing passenger choice, and to understand how such information should best be presented. Crowded trains can adversely affect the experience of rail passengers. They can also cause practical issues for train operators, especially if slow boarding and alighting at stations makes it hard to maintain tight dwell times. The project showed it might possible to mitigate some of these issues by providing better information to passengers and encouraging them to make different travel choices as a result.
More about the “Data to Improve Customer Experience” competition (2015):