28 January 2020 at the Royal Geographical Society (with IBG)
Calculating journey time is a complex geographical data problem for which accurate estimation can be sensitive to the data available and the method or technology adopted. Accurate and consistent calculations of journey times contribute to a shared understanding of the public’s access to key services, help describe the accessibility or connectivity of populations around the UK, as well as improve estate management, and contribute to an understanding of improvements in productivity. However, a range of methods are currently in use by different organisations, departments and agencies.
The event Journey times for policy-making, delivery and evaluation took place at the Society in January 2020. Presentations and discussion explored approaches to, and implications of, journey time calculations across a range of organisations, drawing upon specific case studies. These addressed, amongst other things: methodologies, data requirements, calculation parameters and assumptions, building organisational knowledge and capacity for this work, and finding the right balance around transparency, accuracy, reproducibility and accountability with the tools available.
Over the course of the afternoon, three cross-cutting themes emerged from the presentations, questions and discussion:
the diversity of approaches and opportunities to improving sharing around knowledge, applications and use cases, tools/techniques or data;
journey time as one of multiple levers for policy; and
the interplay between the journey and the journey-maker (the characteristics of ‘user’ populations).
Participants came from a wide range of backgrounds across the public, private and third sectors, but found many challenges and questions in common. The presentations illustrated the richness and versatility of approaches currently in use, and the insights each approach brings for the delivery and management of services and assets.
Participants reflected on the challenges of using different tools or methods to attempt to achieve (broadly) the same outcome. Common challenges included technical or data limitations, such as hardware/infrastructure issues for heavy computing tasks and/or access to good quality data of the right type. In some cases, ‘pieced together’ solutions yielded the desired outcome, but were difficult to sustain or scale, including from local/case study to national analysis.
The sharing of skills and knowledge within and across teams was noted as important, in particular opportunities to share data and technical approaches. Some participants acknowledged that work in their organisation had been initiated by one or two skilled/knowledgeable staff and that knowledge transfer was not always prioritised. Participants discussed the relative merits of in-house solutions vs open-source code/tools/APIs vs third-party products (which may pose a problem for public sector transparency of policy-making or ownership of data if the approach is ‘black box’).
The application of journey time analysis to different geographies, and scales of geographies was also discussed. As one example, the depth of analysis possible for London is not equally possible for all major UK cities, but improvements in open transport data sources (such as the new Bus Open Data service from Department for Transport) may support future work. While participants generally agreed that the insight gained from greater granularity around journey time, especially when combined with other data, was worth the effort, it was noted that greater granularity can lead to a problem of scalability for certain technical approaches, and increasing precision can occasionally lead to unintelligibility in maps/visual representations for non-expert audiences.
Discussions around ‘use cases’ (the reason for undertaking a journey-time analysis in the first place, and how different stakeholders may use this information for what purpose) reflected on the importance of understanding the relationship between properties/locations, people, and broader geographical contexts (including the data held about those). With that in mind, participants discussed the ways in which a technical approach might be selected or adapted to yield the greatest insight from the information available.
The usefulness of journey time calculations as a tool for horizon-scanning and forecasting for future policy decisions was also discussed. Participants noted the ‘power of a map’ when presented to decision-makers, especially for demonstrating ‘before’ and ‘after' scenarios, but also noted frequent requests for 'tweaks' to analysis parameters to understand various scenarios, sometimes with little understanding of the complexity of technique, the underlying assumptions of the analysis, or of what the map/visualisation was actually intended to show. Discussion explored the ways in which those undertaking geospatial analysis have a responsibility to help policy-makers to understand spatial representations to support their use alongside other information for decision-making.
Discussion also addressed the benefits of working at different scales for analysis, and the usefulness of small-scale analysis for understanding user perceptions and experiences. From the perspective of a ‘journey-maker’, the time a journey takes may not be the only deciding factor in making the journey. From the perspective of the policy-maker, journey time is one way of measuring ‘accessibility’ of services or locations; cost to maintain/deliver, availability of alternative options or delivery modes (including digital), and changes in geographical distribution or demographic make-up of user populations are just a few examples of other considerations.
Participants reflected on the risks involved in isolating journey time from other characteristics of journeys, which may include: physical accessibility, cost, congestion, connectivity (e.g. between modes, where some modes are inaccessible or inconvenient to some users), cultural context, robustness or reliability of transport mode, network capacity if many journeys suddenly added or changed, quality of journey experience, time of day (especially where there are implications for outbound or return journeys ‘out of hours’), and user preference. While journey-time is the most nationally comparable measure, it is much harder to address journey choice. The idea of an 'average journey' or 'average user' was challenged, but some participants spoke of the necessity of drawing upon modelling data for 'average' or 'typical' journeys to streamline analysis even as ‘real time’ data become increasingly available.
Part 1 presentations Q&A and discussion
Assessing access to services using multimodal transport networks
Guy Hannay, Data Science Campus, Office for National Statistics
The Logistics of Travel Time Calculations (and Associated Pitfalls)
Patrick Rickles, Head of Business Intelligence and Spatial Data Science, HM Courts and Tribunals Service
Generating granular estimates of job accessibility measures: challenges and opportunities
Stef Garasto, Principal Researcher, Data Science, Creative Economy & Data Analytics, Nesta
Integration of journey times information to support Census 2021 and Census Rehearsal 2019
Niamh Jefford, Geospatial Researcher in Data Architecture, Office for National Statistics
Part 2 presentations, Q&A and discussion
Journey time and connectivity measures for London
Simon Cooper, Principal Analyst, City Planning - Streets Analysis, Transport for London
Modelling public transport with the TravelTime API
Daniel Cronin, Associate - Geospatial Enterprise, Knight Frank
Fair access: towards a transport system for everyone
Helen McKenzie, Senior GIS Consultant, Steer Group
Journey time analysis at the NAO
Marc Adams and Helen Roberts, National Audit Office
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Royal Geographical Society (with IBG) (2020). Journey times for policy-making delivery and evaluation. Available at www.rgs.org/Impact/journeytimes. Last accessed on: <date>
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