Abstract
Ensuring equitable public transit access remains challenging, particularly in densely populated cities like New York City (NYC), where low-income and minority communities often face limited transit accessibility. Bike-sharing systems (BSS) can bridge these equity gaps by providing affordable first- and last-mile connections. However, strategically expanding BSS into underserved neighborhoods is difficult due to uncertain bike-sharing demand at newly planned ("cold-start") station locations and limitations in traditional accessibility metrics that may overlook realistic bike usage potential. We introduce Transit for All (TFA), a spatial computing framework designed to guide the equitable expansion of BSS through three components: (1) spatially-informed bike-sharing demand prediction at cold-start stations using region representation learning that integrates multimodal geospatial data, (2) comprehensive transit accessibility assessment leveraging our novel weighted Public Transport Accessibility Level (wPTAL) by combining predicted bike-sharing demand with conventional transit accessibility metrics, and (3) strategic recommendations for new bike station placements that consider potential ridership and equity enhancement. Using NYC as a case study, we identify transit accessibility gaps that disproportionately impact low-income and minority communities in historically underserved neighborhoods. Our results show that strategically placing new stations guided by wPTAL notably reduces disparities in transit access related to economic and demographic factors. From our study, we demonstrate that TFA provides practical guidance for urban planners to promote equitable transit and enhance the quality of life in underserved urban communities.
Abstract (translated)
确保公共交通的公平准入仍然具有挑战性，特别是在像纽约市（NYC）这样的高人口密度城市中，低收入和少数族裔社区经常面临有限的交通可达性。共享单车系统（BSS）可以通过提供经济实惠的第一公里和最后一公里连接来弥合这些平等差距。然而，由于在新规划站点处不确定的自行车共享需求以及传统可达性指标可能忽视实际自行车使用潜力的限制，向服务不足地区战略性扩展BSS变得困难。 我们引入了Transit for All（TFA），这是一个基于空间计算框架的设计，旨在通过三个组成部分指导共享单车系统的公平扩张：(1) 使用区域表示学习在冷启动站点进行空间信息引导的共享单车需求预测，并整合多模式地理空间数据；(2) 采用我们的新型加权公共交通可达性水平（wPTAL）综合评估全面交通可达性，该指标结合了预测的自行车共享需求与传统的交通可达性指标；(3) 考虑潜在乘客和提升公平性的战略建议为新的自行车站点选址。 以NYC为例作为案例研究，我们识别出了历史上服务不足的社区中低收入和少数族裔群体面临的主要公共交通可达性差距。我们的结果表明，根据wPTAL指导的新站点战略性放置显著减少了与经济和人口统计因素相关的交通访问不平等。通过我们的研究，我们证明了TFA为城市规划者提供了一种实用指南来促进公平的公共交通，并提升服务不足的城市社区的生活质量。
URL
https://arxiv.org/abs/2506.15113
