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In this demonstration, we advocate a federated approach to shared mobility, which enhances its effectiveness by enabling optimizations across platforms while retaining their autonomy. We develop privacy-preserving operators and incentive mechanisms dedicated to supply prediction and task assignment in shared mobility and implement generic interfaces that support diverse prediction and assignment algorithms. We showcase the shared mobility system with real-world ride-hailing applications.<\/jats:p>","DOI":"10.14778\/3685800.3685896","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"4445-4448","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["FedSM: A Practical Federated Shared Mobility System"],"prefix":"10.14778","volume":"17","author":[{"given":"Shuyue","family":"Wei","sequence":"first","affiliation":[{"name":"SKLCCSE Lab, FBPC Beijing Advanced Innovation Center, Beihang University"}]},{"given":"Yuanyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"North China Institute of Computing Technology"}]},{"given":"Zimu","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Data Science, City University of Hong Kong"}]},{"given":"Tianlong","family":"Zhang","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Ke","family":"Xu","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Thomas Cormen Charles Leiserson Ronald Rivest et al. 2009. 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