Elnaz Yousefzadeh Barri
Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms
Yousefzadeh Barri, Elnaz; Farber, Steven; Jahanshahi, Hadi; Beyazit, Eda
Authors
Steven Farber
Hadi Jahanshahi
Eda Beyazit
Abstract
Building an accurate model of travel behaviour based on individuals’ characteristics and built environment attributes is of importance for policy-making and transportation planning. Recent experiments with big data and Machine Learning (ML) algorithms toward a better travel behaviour analysis have mainly overlooked socially disadvantaged groups. Accordingly, in this study, we explore the travel behaviour responses of low-income individuals to transit investments in Greater Toronto and Hamilton Area, Canada, using statistical and ML models. We first investigate how the model choice affects the prediction of transit use by the low-income group. This step includes comparing the predictive performance of traditional and ML algorithms and then evaluating a transit investment policy by contrasting the predicted activities and the spatial distribution of transit trips generated by vulnerable households after improving accessibility. We also empirically investigate the proposed transit investment by each algorithm and compare it with the city of Brampton's future transportation plan. While, unsurprisingly, the ML algorithms outperform classical models, there are still doubts about using them due to interpretability concerns. Hence, we adopt recent local and global model-agnostic interpretation tools to interpret how the model arrives at its predictions. Our findings reveal the great potential of ML algorithms for enhanced travel behaviour predictions for low-income strata without considerably sacrificing interpretability.
Citation
Yousefzadeh Barri, E., Farber, S., Jahanshahi, H., & Beyazit, E. (2022). Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms. Journal of Transport Geography, 105, Article 103482. https://doi.org/10.1016/j.jtrangeo.2022.103482
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 26, 2022 |
Online Publication Date | Nov 15, 2022 |
Publication Date | Dec 31, 2022 |
Deposit Date | Aug 8, 2023 |
Journal | Journal of Transport Geography |
Print ISSN | 0966-6923 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 105 |
Article Number | 103482 |
DOI | https://doi.org/10.1016/j.jtrangeo.2022.103482 |
Public URL | https://uwe-repository.worktribe.com/output/11013017 |
You might also like
Working women and unequal mobilities in the urban periphery
(2019)
Book Chapter
The use of state-of-the-art transport models by policymakers – beauty in simplicity?
(2016)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search