"Equity Promotion in Public Transportation" by Anik Pramanik, Pan Xu et al.
 

Equity Promotion in Public Transportation

Document Type

Conference Proceeding

Publication Date

6-27-2023

Abstract

There are many news articles reporting the obstacles confronting poverty-stricken households in access to public transits. These barriers create a great deal of inconveniences for these impoverished families and more importantly, they contribute a lot of social inequalities. A typical approach addressing the issue is to build more transport infrastructure to offer more opportunities to access the public transits especially for those deprived communities. Examples include adding more bus lines connecting needy residents to railways systems and extending existing bus lines to areas with low socioeconomic status. Recently, a new strategy is proposed, which is to harness the ubiquitous ride-hailing services to connect disadvantaged households with the nearest public transportations. Compared with the former infrastructure-based solution, the ride-hailing-based strategy enjoys a few exclusive benefits such as higher effectiveness and more flexibility. In this paper, we propose an optimization model to study how to integrate the two approaches together for equity-promotion purposes. Specifically, we aim to design a strategy of allocating a given limited budget to different candidate programs such that the overall social equity is maximized, which is defined as the minimum covering ratio among all pre-specified protected groups of households (based on race, income, etc.). We have designed a linear-programming (LP) based rounding algorithm, which proves to achieve an optimal approximation ratio of 1 - 1/e. Additionally, we test our algorithm against a few baselines on real data assembled by outsourcing multiple public datasets collected in the city of Chicago. Experimental results confirm our theoretical predictions and demonstrate the effectiveness of our LP-based strategy in promoting social equity, especially when the budget is insufficient.

Identifier

85168250273 (Scopus)

ISBN

[9781577358800]

Publication Title

Proceedings of the 37th Aaai Conference on Artificial Intelligence Aaai 2023

External Full Text Location

https://doi.org/10.1609/aaai.v37i10.2636126403

First Page

11890

Last Page

11898

Volume

37

Grant

1109012201

Fund Ref

Fundamental Research Funds for the Central Universities

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