Self-organized UAV traffic in realistic environments

No Thumbnail Available
Files
There are no files associated with this item.
Date
2016
Authors
Viragh, Csaba
Gershenson, Carlos
Vasarhelyi, Gabor
Editors
Contact
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
URI (citable link)
DOI (citable link)
ArXiv-ID
International patent number
Link to the license
oops
EU project number
Project
Open Access publication
Collections
Restricted until
Title in another language
Research Projects
Organizational Units
Journal Issue
Publication type
Contribution to a conference collection
Publication status
Published
Published in
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - Piscataway, NJ : IEEE, 2016. - pp. 1645-1652. - eISSN 2153-0866. - ISBN 978-1-5090-3762-9
Abstract
We investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update rate and finite inertia. We implemented two fundamental self-organized algorithms: one with constant direction and one with constant velocity preference to reach a desired target. We performed evolutionary optimization on both algorithms in five basic traffic scenarios and tested the optimized algorithms under different vehicle densities. We provide optimal algorithm and parameter selection criteria and compare the maximal flux and collision risk of each solution and situation. We found that i) different scenarios and densities require different algorithmic approaches, i.e., UAVs have to behave differently in sparse and dense environments or when they have common or different targets; ii) a slower-is-faster effect is implicitly present in our models, i.e., the maximal flux is achieved at densities where the average speed is far from maximal; iii) communication delay is the most severe destabilizing environmental condition that has a fundamental effect on performance and needs to be taken into account when designing algorithms to be used in real life.
Summary in another language
Subject (DDC)
570 Biosciences, Biology
Keywords
Three-dimensional displays, Two dimensional displays, Roads, Trajectory, Mathematical model, Vehicles, Robot sensing systems
Conference
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 9, 2016 - Oct 14, 2016, Daejeon, South Korea
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690VIRAGH, Csaba, Mate NAGY, Carlos GERSHENSON, Gabor VASARHELYI, 2016. Self-organized UAV traffic in realistic environments. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Daejeon, South Korea, Oct 9, 2016 - Oct 14, 2016. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ:IEEE, pp. 1645-1652. eISSN 2153-0866. ISBN 978-1-5090-3762-9. Available under: doi: 10.1109/IROS.2016.7759265
BibTex
@inproceedings{Viragh2016-10Selfo-38186,
  year={2016},
  doi={10.1109/IROS.2016.7759265},
  title={Self-organized UAV traffic in realistic environments},
  isbn={978-1-5090-3762-9},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={1645--1652},
  author={Viragh, Csaba and Nagy, Mate and Gershenson, Carlos and Vasarhelyi, Gabor}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/38186">
    <dc:contributor>Viragh, Csaba</dc:contributor>
    <dcterms:title>Self-organized UAV traffic in realistic environments</dcterms:title>
    <dcterms:issued>2016-10</dcterms:issued>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Viragh, Csaba</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-28T14:11:51Z</dcterms:available>
    <dc:contributor>Vasarhelyi, Gabor</dc:contributor>
    <dc:creator>Vasarhelyi, Gabor</dc:creator>
    <dc:creator>Nagy, Mate</dc:creator>
    <dc:contributor>Nagy, Mate</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/38186"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-28T14:11:51Z</dc:date>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Gershenson, Carlos</dc:creator>
    <dcterms:abstract xml:lang="eng">We investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update rate and finite inertia. We implemented two fundamental self-organized algorithms: one with constant direction and one with constant velocity preference to reach a desired target. We performed evolutionary optimization on both algorithms in five basic traffic scenarios and tested the optimized algorithms under different vehicle densities. We provide optimal algorithm and parameter selection criteria and compare the maximal flux and collision risk of each solution and situation. We found that i) different scenarios and densities require different algorithmic approaches, i.e., UAVs have to behave differently in sparse and dense environments or when they have common or different targets; ii) a slower-is-faster effect is implicitly present in our models, i.e., the maximal flux is achieved at densities where the average speed is far from maximal; iii) communication delay is the most severe destabilizing environmental condition that has a fundamental effect on performance and needs to be taken into account when designing algorithms to be used in real life.</dcterms:abstract>
    <dc:language>eng</dc:language>
    <dc:contributor>Gershenson, Carlos</dc:contributor>
  </rdf:Description>
</rdf:RDF>
Internal note
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Contact
URL of original publication
Test date of URL
Examination date of dissertation
Method of financing
Comment on publication
Alliance license
Corresponding Authors der Uni Konstanz vorhanden
International Co-Authors
Bibliography of Konstanz
Refereed