{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:15:44Z","timestamp":1774120544127,"version":"3.50.1"},"reference-count":28,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2019,6,30]],"date-time":"2019-06-30T00:00:00Z","timestamp":1561852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Spatial Algorithms Syst."],"published-print":{"date-parts":[[2019,6,30]]},"abstract":"<jats:p>The control of large-scale mobility-on-demand systems is an emerging topic that has been considered from a system theoretical, transportation scientific, and algorithmic point of view. Existing formulations model mobility-on-demand systems in a queuing theoretical, network flow-based, or continuous, kinematic framework. In this work, we model a mobility-on-demand system as a stochastic differential equation that represents a generalization of previous approaches. Based on the model, we define system imbalance as the difference of the stochastic processes of service request arrival and vehicle arrival. We formally derive the first moment of the system imbalance for an imbalance control strategy that consists of a feedforward control approach (reference trajectory) and an additional feedback component. A distributed feedback control policy is defined that averages the imbalance across the system and therefore aims at a uniform quality of service distribution. Finally, we verify our results in a high-fidelity and large-scale agent-based simulation of a hypothetical mobility-on-demand system.<\/jats:p>","DOI":"10.1145\/3325914","type":"journal-article","created":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T19:05:16Z","timestamp":1565809516000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Imbalance in Mobility-on-Demand Systems"],"prefix":"10.1145","volume":"5","author":[{"given":"Marc","family":"Albert","sequence":"first","affiliation":[{"name":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Claudio","family":"Ruch","sequence":"additional","affiliation":[{"name":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emilio","family":"Frazzoli","sequence":"additional","affiliation":[{"name":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,8,14]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3267305.3274156"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ECC.2014.6862386"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2013.2267810"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Guiyun Feng Guangwen Kong and Zizhuo Wang. 2017. We are on the way: Analysis of on-demand ride-hailing systems. Available at SSRN 2960991.  Guiyun Feng Guangwen Kong and Zizhuo Wang. 2017. We are on the way: Analysis of on-demand ride-hailing systems. Available at SSRN 2960991.","DOI":"10.2139\/ssrn.2960991"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/0361198106198600112"},{"key":"e_1_2_1_7_1","unstructured":"Claudio Ruch Spencer Richards and Emilio Frazzoli. 2019. The price of anarchy in mobility-on-demand systems.  Claudio Ruch Spencer Richards and Emilio Frazzoli. 2019. The price of anarchy in mobility-on-demand systems."},{"key":"e_1_2_1_8_1","unstructured":"Sebastian H\u00f6rl Claudio Ruch Felix Becker Emilio Frazzoli and Kay W. Axhausen. 2017. Fleet control algorithms for automated mobility: A simulation assessment for Zurich. Arbeitsberichte Verkehrs-und Raumplanung 1270 (2017).  Sebastian H\u00f6rl Claudio Ruch Felix Becker Emilio Frazzoli and Kay W. Axhausen. 2017. Fleet control algorithms for automated mobility: A simulation assessment for Zurich. Arbeitsberichte Verkehrs-und Raumplanung 1270 (2017)."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2013.2259993"},{"key":"e_1_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Rainer E. Burkard and Eranda Cela. 1999. Linear assignment problems and extensions. In Handbook of Combinatorial Optimization. Springer 75--149.  Rainer E. Burkard and Eranda Cela. 1999. Linear assignment problems and extensions. In Handbook of Combinatorial Optimization. Springer 75--149.","DOI":"10.1007\/978-1-4757-3023-4_2"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2010.5717552"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364912444766"},{"key":"e_1_2_1_13_1","unstructured":"Rick Zhang. 2016. Models and Large-scale Coordination Algorithms for Autonomous Mobility-on-demand. Ph.D. Dissertation. Stanford University.  Rick Zhang. 2016. Models and Large-scale Coordination Algorithms for Autonomous Mobility-on-demand. Ph.D. Dissertation. Stanford University."},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the American Control Conference (ACC\u201916)","author":"Spieser K."},{"key":"e_1_2_1_15_1","unstructured":"Rick Zhang Federico Rossi and Marco Pavone. 2015. Model predictive control of autonomous mobility-on-demand systems. arxiv:cs.SY\/1509.03985  Rick Zhang Federico Rossi and Marco Pavone. 2015. Model predictive control of autonomous mobility-on-demand systems. arxiv:cs.SY\/1509.03985"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364915581863"},{"key":"e_1_2_1_17_1","volume-title":"Accessed","author":"Geering H. P.","year":"2019"},{"key":"e_1_2_1_18_1","unstructured":"Klaus Bichteler. 2010. Stochastic Integration with Jumps. Cambridge University Press.  Klaus Bichteler. 2010. Stochastic Integration with Jumps. Cambridge University Press."},{"key":"e_1_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Floyd B. Hanson. 2007. Applied Stochastic Processes and Control for Jump-Diffusions: Modeling Analysis and Computation. Society for Industrial and Applied Mathematics.   Floyd B. Hanson. 2007. Applied Stochastic Processes and Control for Jump-Diffusions: Modeling Analysis and Computation. Society for Industrial and Applied Mathematics.","DOI":"10.1137\/1.9780898718638"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2006.887293"},{"key":"e_1_2_1_21_1","unstructured":"Roger A. Horn and Charles R. Johnson. 2013. Matrix Analysis. Cambridge University Press.   Roger A. Horn and Charles R. Johnson. 2013. Matrix Analysis. Cambridge University Press."},{"key":"e_1_2_1_22_1","unstructured":"Francesco Bullo. 2016. Lectures on network systems. Kindle Direct Publishing.  Francesco Bullo. 2016. Lectures on network systems. Kindle Direct Publishing."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.2016.7525011"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460966"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569961"},{"key":"e_1_2_1_26_1","unstructured":"Andreas Horni Kai Nagel and Kay W. Axhausen. 2016. The Multi-agent Transport Simulation MATSim. Ubiquity Press London.   Andreas Horni Kai Nagel and Kay W. Axhausen. 2016. The Multi-agent Transport Simulation MATSim. Ubiquity Press London."},{"key":"e_1_2_1_27_1","unstructured":"AMoDeus Platform. {n.d.}. Retrieved from https:\/\/www.amodeus.science.  AMoDeus Platform. {n.d.}. Retrieved from https:\/\/www.amodeus.science."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5555\/1702135.1702171"},{"key":"e_1_2_1_29_1","volume-title":"Robotics: Science and Systems VII","author":"Pavone M.","year":"2011"}],"container-title":["ACM Transactions on Spatial Algorithms and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3325914","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3325914","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:53:08Z","timestamp":1750204388000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3325914"}},"subtitle":["A Stochastic Model and Distributed Control Approach"],"short-title":[],"issued":{"date-parts":[[2019,6,30]]},"references-count":28,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,6,30]]}},"alternative-id":["10.1145\/3325914"],"URL":"https:\/\/doi.org\/10.1145\/3325914","relation":{},"ISSN":["2374-0353","2374-0361"],"issn-type":[{"value":"2374-0353","type":"print"},{"value":"2374-0361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,30]]},"assertion":[{"value":"2018-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-04-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}