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Database Syst."],"published-print":{"date-parts":[[2022,3,31]]},"abstract":"<jats:p>\n            There has been a dramatic growth of shared mobility applications such as ride-sharing, food delivery, and crowdsourced parcel delivery. Shared mobility refers to transportation services that are shared among users, where a central issue is\n            <jats:italic>route planning<\/jats:italic>\n            . Given a set of workers and requests, route planning finds for each worker a route, i.e., a sequence of locations to pick up and drop off passengers\/parcels that arrive from time to time, with different optimization objectives. Previous studies lack practicability due to their conflicted objectives and inefficiency in inserting a new request into a route, a basic operation called\n            <jats:italic>insertion<\/jats:italic>\n            . In addition, previous route planning solutions fail to exploit the appearance patterns of future requests hidden in historical data for optimization. In this paper, we present a unified formulation of route planning called URPSM. It has a well-defined parameterized objective function which eliminates the contradicted objectives in previous studies and enables flexible multi-objective route planning for shared mobility. We propose two insertion-based frameworks to solve the URPSM problem. The first is built upon the\n            <jats:italic>plain-insertion<\/jats:italic>\n            widely used in prior studies, which processes online requests only, whereas the second relies on a new insertion operator called\n            <jats:italic>prophet-insertion<\/jats:italic>\n            that handles both online and predicted requests. Novel dynamic programming algorithms are designed to accelerate both insertions to only linear time. Theoretical analysis shows that no online algorithm can have a constant competitive ratio for the URPSM problem under the competitive analysis model, yet our prophet-insertion-based framework can achieve a constant optimality ratio under the instance-optimality model. Extensive experimental results on real datasets show that our insertion-based solutions outperform the state-of-the-art algorithms in both effectiveness and efficiency by a large margin (e.g., up to 30\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\( \\times \\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            more effective in the objective and up to 20\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\( \\times \\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            faster).\n          <\/jats:p>","DOI":"10.1145\/3488723","type":"journal-article","created":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T12:28:18Z","timestamp":1651494498000},"page":"1-48","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":42,"title":["Unified Route Planning for Shared Mobility: An Insertion-based Framework"],"prefix":"10.1145","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5598-0312","authenticated-orcid":false,"given":"Yongxin","family":"Tong","sequence":"first","affiliation":[{"name":"SKLSDE Lab and IRI, Beihang University, Beijing, China"}]},{"given":"Yuxiang","family":"Zeng","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong SAR, China"}]},{"given":"Zimu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8257-5806","authenticated-orcid":false,"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong SAR, China"}]},{"given":"Ke","family":"Xu","sequence":"additional","affiliation":[{"name":"SKLSDE Lab and IRI, Beihang University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2022,5,2]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611675114"},{"key":"e_1_3_5_3_2","first-page":"3:1\u20133:10","volume-title":"SIGSPATIAL","author":"Asghari Mohammad","year":"2016","unstructured":"Mohammad Asghari, Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, and Yaguang Li. 2016. 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