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Optimal On-the-fly Route Planning with Rich Transportation Requests
Lehigh University, Bethlehem, PA, USA.ORCID iD: 0000-0002-1132-1462
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-4173-2593
Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID iD: 0000-0002-2225-7275
University of Maryland, College Park, MD, USA.ORCID iD: 0000-0002-7141-2657
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2025 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 41, p. 4041-4056Article in journal (Refereed) Published
Abstract [en]

The paper considers the route planning problem for a vehicle with limited capacity operating in a road network. The vehicle is assigned a set of transportation requests that are more complex than traveling between two locations, may involve dependencies between their sub-tasks, and include deadlines and priorities. The requests arrive gradually over the deployment time-horizon, and thus replanning is needed for new requests. We address cases when not all requests can be serviced by their deadlines despite car sharing. We introduce multiple quality measures for plans that account for requests' delays with respect to deadlines and priorities. We formalize the problem as planning in a weighted transition system under syntactically co-safe LTL formulas. We develop an online planning and replanning algorithm based on the automata-based approach to least-violating plan synthesis and on translation to a Mixed Integer Linear Program (MILP). Furthermore, we show that the MILP reduces to graph search for a subclass of quality measures that satisfy a monotonicity property. We show the approach in simulations, including a case study on the mid-Manhattan road network over the span of 24 hours.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025. Vol. 41, p. 4041-4056
Keywords [en]
Autonomous Agents, MILP, Mobility on Demand, Route Planning, Temporal Logic
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-366024DOI: 10.1109/TRO.2025.3577010ISI: 001518714500007Scopus ID: 2-s2.0-105007602066OAI: oai:DiVA.org:kth-366024DiVA, id: diva2:1980958
Note

QC 20250703

Available from: 2025-07-03 Created: 2025-07-03 Last updated: 2025-09-24Bibliographically approved

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Tumova, Jana

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