Equitable Public Bus Network Optimization for Social Good: A Case Study of Singapore
Published in Proceedings of the 2022 ACM Conference on Fairness, Accountability and Transparency (FAccT 2022), 2022
Recommended citation: David Tedjopurnomo, Zhifeng Bao, Farhana Choudhury, Hui Luo, and A. K. Qin. "Equitable public bus network optimization for social good: A case study of singapore." In 2022 ACM Conference on Fairness, Accountability, and Transparency, page 278–288, 2022. https://dl.acm.org/doi/10.1145/3531146.3533092
Public bus transport is a major backbone of many cities’ socioeconomic activities. As such, the topic of public bus network optimization has received substantial attention in Geographic Information System (GIS) research. Unfortunately, most of the current literature are focused on improving only the efficiency of the bus network, neglecting the important equity factors. Optimizing only the efficiency of a bus network may cause these limited public transportation resources to be shifted away from areas with disadvantaged demographics, compounding the equity problem. In this work, we make the first attempt to explore the intricacies of the equitable public bus network optimization problem by performing a case study of Singapore’s public bus network. We describe the challenges in designing an equitable public bus network, tackle the fundamental problem of formulating efficiency and equity metrics, perform exploratory experiments to assess each metric’s real-life impact, and analyze the challenges of the equitable bus network optimization task. For our experiments, we have curated and combined Singapore’s bus network data, road network data, census area boundaries data, and demographics data into a unified dataset which we released publicly. Our objective is not only to explore this important yet relatively unexplored problem, but also to inspire more discussion and research.
DOI: https://doi.org/10.1145/3531146.3533092