{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T16:13:24Z","timestamp":1758125604748,"version":"3.37.3"},"reference-count":12,"publisher":"Walter de Gruyter GmbH","issue":"4","funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"crossref","award":["Unassigned"],"award-info":[{"award-number":["Unassigned"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Trajectory planning for autonomous cars can be addressed by primitive-based methods, which encode nonlinear dynamical system behavior into automata. In this paper, we focus on optimal trajectory planning. Since, typically, multiple criteria have to be taken into account, multiobjective optimization problems have to be solved. For the resulting Pareto-optimal motion primitives, we introduce a universal automaton, which can be reduced or reconfigured according to prioritized criteria during planning. We evaluate a corresponding multi-vehicle planning scenario with both simulations and laboratory experiments.<\/jats:p>","DOI":"10.1515\/auto-2022-0158","type":"journal-article","created":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T01:37:55Z","timestamp":1680831475000},"page":"294-300","source":"Crossref","is-referenced-by-count":1,"title":["Optimization-based motion primitive automata for autonomous driving"],"prefix":"10.1515","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5238-7786","authenticated-orcid":false,"given":"Matheus V. A.","family":"Pedrosa","sequence":"first","affiliation":[{"name":"Chair of Systems Modeling and Simulation, Systems Engineering , Saarland University , Saarbr\u00fccken , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Scheffe","sequence":"additional","affiliation":[{"name":"Chair for Embedded Software , RWTH Aachen University , Aachen , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bassam","family":"Alrifaee","sequence":"additional","affiliation":[{"name":"Chair for Embedded Software , RWTH Aachen University , Aachen , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kathrin","family":"Fla\u00dfkamp","sequence":"additional","affiliation":[{"name":"Chair of Systems Modeling and Simulation, Systems Engineering , Saarland University , Saarbr\u00fccken , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2023,4,7]]},"reference":[{"key":"2023060517421230150_j_auto-2022-0158_ref_001","unstructured":"K. Fla\u00dfkamp, \u201cOn the optimal control of mechanical systems \u2013 hybrid control strategies and hybrid dynamics,\u201d Ph.D. thesis, University of Paderborn, 2013."},{"key":"2023060517421230150_j_auto-2022-0158_ref_002","doi-asserted-by":"crossref","unstructured":"M. Kloock, P. Scheffe, J. Maczijewski, et al.., \u201cCyber-Physical Mobility Lab: an open-source platform for networked and autonomous vehicles,\u201d in 2021 European Control Conference (ECC), pp.\u00a01937\u20131944, 2021.","DOI":"10.23919\/ECC54610.2021.9654986"},{"key":"2023060517421230150_j_auto-2022-0158_ref_003","doi-asserted-by":"crossref","unstructured":"E. Frazzoli, M. A. Dahleh, and E. Feron, \u201cManeuver-based motion planning for nonlinear systems with symmetries,\u201d IEEE Trans. Robot., vol.\u00a021, no.\u00a06, pp.\u00a01077\u20131091, 2005. https:\/\/doi.org\/10.1109\/tro.2005.852260.","DOI":"10.1109\/TRO.2005.852260"},{"key":"2023060517421230150_j_auto-2022-0158_ref_004","doi-asserted-by":"crossref","unstructured":"M. Althoff, M. Koschi, and S. Manzinger, \u201cCommonroad: composable benchmarks for motion planning on roads,\u201d in Proc. of the IEEE Intelligent Vehicles Symposium, 2017.","DOI":"10.1109\/IVS.2017.7995802"},{"key":"2023060517421230150_j_auto-2022-0158_ref_005","doi-asserted-by":"crossref","unstructured":"P. Scheffe, M. V. A. Pedrosa, K. Fla\u00dfkamp, and B. Alrifaee, \u201cReceding horizon control using graph search for multi-agent trajectory planning,\u201d IEEE Trans. Control Syst. Technol., pp.\u00a01\u201314, 2022, https:\/\/doi.org\/10.1109\/tcst.2022.3214718.","DOI":"10.36227\/techrxiv.16621963"},{"key":"2023060517421230150_j_auto-2022-0158_ref_006","doi-asserted-by":"crossref","unstructured":"M. V. A. Pedrosa, T. Schneider, and K. Fla\u00dfkamp, \u201cLearning motion primitives automata for autonomous driving applications,\u201d Math. Comput. Appl., vol.\u00a027, no.\u00a04, p.\u00a054, 2022. https:\/\/doi.org\/10.3390\/mca27040054.","DOI":"10.3390\/mca27040054"},{"key":"2023060517421230150_j_auto-2022-0158_ref_007","doi-asserted-by":"crossref","unstructured":"K. Fla\u00dfkamp, S. Ober-Bl\u00f6baum, and K. Worthmann, \u201cSymmetry and motion primitives in model predictive control,\u201d Math. Control Signals Syst., vol.\u00a031, pp.\u00a0455\u2013485, 2019. https:\/\/doi.org\/10.1007\/s00498-019-00246-7.","DOI":"10.1007\/s00498-019-00246-7"},{"key":"2023060517421230150_j_auto-2022-0158_ref_008","doi-asserted-by":"crossref","unstructured":"M. V. A. Pedrosa, T. Schneider, and K. Fla\u00dfkamp, \u201cGraph-based motion planning with primitives in a continuous state space search,\u201d in 2021 6th International Conference on Mechanical Engineering and Robotics Research (ICMERR), 2021, pp.\u00a030\u201339.","DOI":"10.1109\/ICMERR54363.2021.9680825"},{"key":"2023060517421230150_j_auto-2022-0158_ref_009","doi-asserted-by":"crossref","unstructured":"M. Naumann, M. Lauer, and C. Stiller, \u201cGenerating comfortable, safe and comprehensible trajectories for automated vehicles in mixed traffic,\u201d in 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018, pp.\u00a0575\u2013582.","DOI":"10.1109\/ITSC.2018.8569658"},{"key":"2023060517421230150_j_auto-2022-0158_ref_010","doi-asserted-by":"crossref","unstructured":"P. Scheffe, G. Dorndorf, and B. Alrifaee, \u201cIncreasing feasibility with dynamic priority assignment in distributed trajectory planning for road vehicles,\u201d in 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022, pp.\u00a03873\u20133879.","DOI":"10.1109\/ITSC55140.2022.9922028"},{"key":"2023060517421230150_j_auto-2022-0158_ref_011","doi-asserted-by":"crossref","unstructured":"B. Alrifaee, F. J. He\u00dfeler, and D. Abel, \u201cCoordinated non-cooperative distributed model predictive control for decoupled systems using graphs,\u201d IFAC-PapersOnLine, vol.\u00a049, no.\u00a022, pp.\u00a0216\u2013221, 2016. https:\/\/doi.org\/10.1016\/j.ifacol.2016.10.399.","DOI":"10.1016\/j.ifacol.2016.10.399"},{"key":"2023060517421230150_j_auto-2022-0158_ref_012","doi-asserted-by":"crossref","unstructured":"P. Scheffe, J. Maczijewski, M. Kloock, et al.., \u201cNetworked and autonomous model-scale vehicles for experiments in research and education,\u201d IFAC-PapersOnLine, vol.\u00a053, no.\u00a02, pp.\u00a017332\u201317337, 2020. https:\/\/doi.org\/10.1016\/j.ifacol.2020.12.1821.","DOI":"10.1016\/j.ifacol.2020.12.1821"}],"container-title":["at - Automatisierungstechnik"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2022-0158\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2022-0158\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,5]],"date-time":"2023-06-05T17:42:40Z","timestamp":1685986960000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2022-0158\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,1]]},"references-count":12,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4,7]]},"published-print":{"date-parts":[[2023,4,25]]}},"alternative-id":["10.1515\/auto-2022-0158"],"URL":"https:\/\/doi.org\/10.1515\/auto-2022-0158","relation":{},"ISSN":["0178-2312","2196-677X"],"issn-type":[{"type":"print","value":"0178-2312"},{"type":"electronic","value":"2196-677X"}],"subject":[],"published":{"date-parts":[[2023,4,1]]}}}