| OpenTripPlanner for R M Morgan, M Young, R Lovelace, L Hama Journal of Open Source Software 4 (44), 1926, 2019 | 35 | 2019 |
| Railway station choice modelling: a review of methods and evidence M Young, S Blainey Transport Reviews 38 (2), 232-251, 2018 | 25 | 2018 |
| OpenTripPlanner - creating and querying your own multi-modal route planner M Young URL: https://github.com/marcusyoung/otp-tutorial, 2018 | 14 | 2018 |
| Development of railway station choice models to improve the representation of station catchments in rail demand models MA Young, SP Blainey Transportation Planning and Technology 41 (1), 80-103, 2017 | 8 | 2017 |
| An automated framework to derive model variables from open transport data using R, PostgreSQL and OpenTripPlanner M Young 24th GIS research UK conference, Greenwich, United Kingdom, 2016 | 7 | 2016 |
| otpr: An API wrapper for OpenTripPlanner M Young | 6* | 2020 |
| Defining probability-based rail station catchments for demand modelling M Young, S Blainey 48th Annual UTSG Conference, Bristol, GB, 2016 | 6 | 2016 |
| A transferable method for estimating the economic impacts of track interventions: Application to ground-borne noise reduction measures for whole sections of route M Young, G Rempelos, E Ntotsios, S Blainey, D Thompson, J Preston Proceedings of the Institution of Mechanical Engineers, Part F: Journal of …, 2021 | 5 | 2021 |
| An automated online tool to forecast demand for new railway stations and analyse potential abstraction effects M Young, S Blainey, T Gowland, S Nagella | 3 | 2019 |
| Development of integrated demand and station choice models for local railway stations and services M Young Proceedings of the 2017 European Transport Conference, Barcelona, Spain, 2017 | 2 | 2017 |
| Developing railway station choice models to improve rail industry demand models M Young | 2 | 2017 |
| Understanding Active Travel Networks Using GPS Data from an Outdoor Mapping App MA Young 12th International Conference on Geographic Information Science (GIScience …, 2023 | | 2023 |
| A comparative assessment of methods for constructing historical geospatial networks of night train services in Europe S Blainey, M Young, J Armstrong | | 2022 |
| A comparative assessment of journey time benefits from different HSR station locations ET Yazici, S Blainey, M Young | | 2022 |
| Station demand forecasting tool M Young, S Blainey Zenodo, 2020 | | 2020 |
| Dataset for A transferable method for estimating the economic impacts of track interventions: application to ground-borne noise reduction measures for whole sections of route M Young, E Ntotsios, G Rempelos University of Southampton, 2020 | | 2020 |
| Modelling railway station choice: can probabilistic catchments improve demand forecasts for new stations? M Young University of Southampton, 2019 | | 2019 |
| Dataset for Development of railway station choice models to improve the representation of station catchments in rail demand models M Young University of Southampton, 2017 | | 2017 |
| Modelling railway station choice: Improving railway station demand forecasting models using probability-based catchments M Young | | 2017 |
| A segment-based spatial analysis of non-motorised road traffic casualties occurring in non built-up areas of England and Wales, 1999-2008. MA Young | | 2010 |
Simon BlaineyProfessor of Sustainable Transport, University of SouthamptonVerified email at soton.ac.uk
