Papers for

urban developers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Origin-destination travel data detailed by mode and purpose for england and wales

Travel Mode- and Purpose-Specific Origin-Destination Matrices for England and Wales from Fused Travel Survey and Mobile Network Data

Abstract: Origin-destination (OD) matrices sit behind much of quantitative transport planning, from model calibration and accessibility analysis to the appraisal of new services and development. The increasing emphasis on place-based solutions requires mobility data that can support decision-making not only at the strategic level, but also at finer spatial scales. This requires up-to-date OD evidence at small-area resolution, disaggregated by travel mode and purpose, which remains either inaccessible or unavailable. In this work, we present dense MSOA-to-MSOA OD matrices for England and Wales, segmented by seven travel modes and representative time periods, with eight trip purposes for the weekday morning peak. The matrices are built by calibrating aggregate mobile network data provided by BT against National Travel Survey (NTS), census and trip-rate evidence, preserving the observed spatial structure of movement while referencing its age, mode and purpose composition to the survey. The open-source data processing pipeline is released alongside the matrices, so that the construction of the dataset can be inspected in full and adapted to other years, regions or assumptions.

Tue 29 SeptComputers and Society
The gist
Transport planners need detailed data about how people travel between places to make better decisions about roads, buses, and trains. The authors combined mobile phone movement data with traditional travel surveys to create detailed maps showing trips by different travel modes and travel reasons across small areas in England and Wales. This new data helps reveal not just where people go, but how and why, with updates for current travel patterns. They also shared the full process publicly so others can create similar datasets for other times or regions.
Open → 2609.36466v1