kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multi-Criteria Evaluation for Sorting Motion Planner Alternatives
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics. KTH, School of Engineering Sciences (SCI), Centres, VinnExcellence Center for ECO2 Vehicle design.ORCID iD: 0000-0002-5233-637x
Cranfield Univ, Adv Vehicle Engn Ctr, Sch Aerosp Transport & Mfg, Cranfield MK43 0AL, Beds, England..
Cranfield Univ, Adv Vehicle Engn Ctr, Sch Aerosp Transport & Mfg, Cranfield MK43 0AL, Beds, England..
Cranfield Univ, Adv Vehicle Engn Ctr, Sch Aerosp Transport & Mfg, Cranfield MK43 0AL, Beds, England..
Show others and affiliations
2022 (English)In: Sensors, E-ISSN 1424-8220, Vol. 22, no 14, p. 5177-, article id 5177Article in journal (Refereed) Published
Abstract [en]

Automated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put their wide impact at risk, as well as their acceptance by the public. In this direction, this paper presents the application of motion planning in order to minimise motion sickness in automated vehicles. Thus, an optimal control problem is formulated through which we seek the optimum velocity profile for a predefined road path for multiple fixed journey time (JT) solutions. In this way, a Pareto Front will be generated for the conflicting objectives of MS and JT. Despite the importance of optimising both of these, the optimum velocity profile should be selected after taking into consideration additional objectives. Therefore, as the optimal control is focused on the MS minimisation, a sorting algorithm is applied to seek the optimum solution among the pareto alternatives of the fixed time solutions. The aim is that this solution will correspond to the best velocity profile that also ensures the optimum compromise between motion comfort, safety and driving behaviour, energy efficiency, journey time and riding confidence.

Place, publisher, year, edition, pages
MDPI AG , 2022. Vol. 22, no 14, p. 5177-, article id 5177
Keywords [en]
automated vehicles, motion planning, sorting alternatives, motion sickness, safety, energy efficiency, journey time
National Category
Vehicle and Aerospace Engineering Applied Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-316251DOI: 10.3390/s22145177ISI: 000834473300001PubMedID: 35890856Scopus ID: 2-s2.0-85135108473OAI: oai:DiVA.org:kth-316251DiVA, id: diva2:1686972
Note

QC 20220812

Available from: 2022-08-12 Created: 2022-08-12 Last updated: 2025-02-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Papaioannou, Georgios

Search in DiVA

By author/editor
Papaioannou, GeorgiosLongo, Stefano
By organisation
Vehicle Engineering and Solid MechanicsVinnExcellence Center for ECO2 Vehicle design
In the same journal
Sensors
Vehicle and Aerospace EngineeringApplied Mechanics

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 44 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf