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Defining probability-based rail station catchments for demand modelling

Defining probability-based rail station catchments for demand modelling
Defining probability-based rail station catchments for demand modelling
The aggregate models commonly used in the UK to estimate demand for new local rail stations require the station catchment to be defined first, so that inputs into the model, such as the population from which demand will be generated, can be specified. The methods typically used to define the catchment implicitly assume that station choice is a deterministic process, and that stations exist in isolation from each other. However, studies show that pre-defined catchments account for only 50-60 percent of observed trips, choice of station is not homogeneous within zones, catchments overlap, and catchments vary by access mode and station type. This paper describes early work to implement an alternative probability-based approach, through the development of a station choice prediction model. To derive realistic station access journey explanatory variables, a routable multi-modal network, incorporating data from OpenStreetMap, the Traveline National Data Set and National Rail timetable, was built using OpenTripPlanner and queried using an API wrapper developed in R. Results from a series of multinomial logit models are presented and a method for generating probabilistic catchments using estimated parameter values is described. An example probabilistic catchment is found to provide a realistic representation of the observed catchment, and to perform better than deterministic catchments.
railway station choice, discrete choice models, station catchments, passenger demand forecasting, open data
Young, Marcus
b7679822-1e61-47d0-b7bf-3e33a12fa8fe
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Young, Marcus
b7679822-1e61-47d0-b7bf-3e33a12fa8fe
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb

Young, Marcus and Blainey, Simon (2016) Defining probability-based rail station catchments for demand modelling. 48th Annual UTSG Conference, United Kingdom. 06 - 08 Jan 2016. 12 pp . (doi:10.13140/RG.2.1.3767.7205).

Record type: Conference or Workshop Item (Paper)

Abstract

The aggregate models commonly used in the UK to estimate demand for new local rail stations require the station catchment to be defined first, so that inputs into the model, such as the population from which demand will be generated, can be specified. The methods typically used to define the catchment implicitly assume that station choice is a deterministic process, and that stations exist in isolation from each other. However, studies show that pre-defined catchments account for only 50-60 percent of observed trips, choice of station is not homogeneous within zones, catchments overlap, and catchments vary by access mode and station type. This paper describes early work to implement an alternative probability-based approach, through the development of a station choice prediction model. To derive realistic station access journey explanatory variables, a routable multi-modal network, incorporating data from OpenStreetMap, the Traveline National Data Set and National Rail timetable, was built using OpenTripPlanner and queried using an API wrapper developed in R. Results from a series of multinomial logit models are presented and a method for generating probabilistic catchments using estimated parameter values is described. An example probabilistic catchment is found to provide a realistic representation of the observed catchment, and to perform better than deterministic catchments.

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More information

Published date: 7 January 2016
Venue - Dates: 48th Annual UTSG Conference, United Kingdom, 2016-01-06 - 2016-01-08
Keywords: railway station choice, discrete choice models, station catchments, passenger demand forecasting, open data
Organisations: Transportation Group

Identifiers

Local EPrints ID: 384539
URI: https://eprints.soton.ac.uk/id/eprint/384539
PURE UUID: 6d9fa1a3-2bd3-44ae-a540-658bfb0b0dfd
ORCID for Marcus Young: ORCID iD orcid.org/0000-0003-4627-1116
ORCID for Simon Blainey: ORCID iD orcid.org/0000-0003-4249-8110

Catalogue record

Date deposited: 12 Jan 2016 14:45
Last modified: 27 Feb 2019 01:21

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