SOURCE-LINKED INTELLIGENCE
Toward Equitable Low-Carbon Mobility: Fairness-Aware Demand Prediction for Expanding Bike-Sharing Systems
Bike-sharing systems are an important component of low-carbon urban mobility, but continued expansion creates challenges in both cold-start prediction and equitable resource allocation. Newly deployed stations lack historical ridership records, causing a mismatch between training and inference for graph-based models on evolving networks. Historical demand may also encode structural inequalities, as lower ridership in low-income neighborhoods can reflect limited infrastructure access rather than weak latent demand. Models trained directly on such data may therefore reinforce existing mobility d
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T22:57:40.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.