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Multi-vehicle motion planning for social optimal mobility-on-demand
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH Royal Inst Technol, Stockholm, Sweden..
MIT, Cambridge, MA 02139 USA..
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH Royal Inst Technol, Stockholm, Sweden..ORCID iD: 0000-0003-4173-2593
MIT, Cambridge, MA 02139 USA..
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2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE COMPUTER SOC , 2018, p. 7298-7305Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we consider a fleet of self-driving cars operating in a road network governed by rules of the road, such as the Vienna Convention on Road Traffic, providing rides to customers to serve their demands with desired deadlines. We focus on the associated motion planning problem that tradesoff the demands' delays and level of violation of the rules of the road to achieve social optimum among the vehicles. Due to operating in the same environment, the interaction between the cars must be taken into account, and can induce further delays. We propose an integrated route and motion planning approach that achieves scalability with respect to the number of cars by resolving potential collision situations locally within so-called bubble spaces enclosing the conflict. The algorithms leverage the road geometries, and perform joint planning only for lead vehicles in the conflict and use queue scheduling for the remaining cars. Furthermore, a framework for storing previously resolved conflict situations is proposed, which can be use for quick querying of joint motion plans. We show the mobility-on-demand setup and effectiveness of the proposed approach in simulated case studies involving up to 10 selfdriving vehicles.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC , 2018. p. 7298-7305
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-237168ISI: 000446394505081Scopus ID: 2-s2.0-85063127749ISBN: 978-1-5386-3081-5 (print)OAI: oai:DiVA.org:kth-237168DiVA, id: diva2:1258288
Conference
IEEE International Conference on Robotics and Automation (ICRA), MAY 21-25, 2018, Brisbane, AUSTRALIA
Funder
Swedish Research Council
Note

QC 20181024

Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2019-05-16Bibliographically approved

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Karlsson, JesperTumova, Jana

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  • apa
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Output format
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