Understanding urban rail travel for improved patronage forecasting
Zheng, Zuduo, Wijeweera, Albert, Sloan, Keith, Washington, Simon, Hyland, Paul, To, Hong, Charles, Michael, Webb, Melissa, Primerano, Frank, Molloy, Andrew, Howells, Louise, Liu, Yulin, Clarris, Heidi, & Holyoak, Nicholas (2013) Understanding urban rail travel for improved patronage forecasting. CRC for Rail Innovation, Brisbane, Qld.
Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities.
This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios.
Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users.
The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.
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|Keywords:||rail transit, patronage forecasting, public transit, travel behaviour|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500)|
|Divisions:||Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Civil Engineering & Built Environment
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||2013 Southern Cross University|
|Copyright Statement:||This work is copyright. Apart from any use permitted under the Copyright Act 1968, no part may be reproduced by any process, nor may any other exclusive right be exercised, without the permission of Southern Cross University.|
|Deposited On:||19 Apr 2016 05:05|
|Last Modified:||20 Apr 2016 03:14|
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