Predicting Ridership at railway intersection Station based on Accessibility Model

DOI

10.2991/icence-16.2016.55How to use a DOI?

Keywords

Traffic engineering; railway intersection; ridership; accessibility; negative logistic function; GIS

Abstract

This paper explores a ridership forecasting method based on railway intersection site accessibility and vehicle use patterns. The accessibility model utilizes vehicle use and demographic data. In the study, we employ GIS to disaggregate population data into small raster cells. Based on the distance decay theory, we apply the negative logistic function in an accessibility model. Total amount of passenger flow is obtained by combining population locations with probability of travel to the railway intersection. The parameters, which play a key role in the accessibility model, are tested in an empirical study of Wuhan, China. Through proper parameter configuration, the accessibility model may achieve acceptable accuracy for predicting railway intersection trip production.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Caixia Han
PY  - 2016/09
DA  - 2016/09
TI  - Predicting Ridership at railway intersection Station based on Accessibility Model
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 259
EP  - 262
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.55
DO  - 10.2991/icence-16.2016.55
ID  - Han2016/09
ER  -