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
Spatial Model Predictive Control for Smooth and Accurate Steering of an Autonomous Truck
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6802-7520
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3672-5316
Show others and affiliations
2017 (English)In: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, Vol. 2, no 4, p. 238-250Article in journal (Refereed) Published
Abstract [en]

In this paper, we present an algorithm for lateral control of a vehicle – a smooth and accurate model predictive controller. The fundamental difference compared to a standard MPC is that the driving smoothness is directly addressed in the cost function. The controller objective is based on the minimization of the first- and second-order spatial derivatives of the curvature. By doing so, jerky commands to the steering wheel, which could lead to permanent damage on the steering components and vehicle structure, are avoided. A good path tracking accuracy is ensured by adding constraints to avoid deviations from the reference path. Finally, the controller is experimentally tested and evaluated on a Scania construction truck. The evaluation is performed at Scania’s facilities near So ̈derta ̈lje, Sweden via two different paths: a precision track that resembles a mining scenario and a high-speed test track that resembles a highway situation. Even using a linearized kinematic vehicle to predict the vehicle motion, the performance of the proposed controller is encouraging, since the deviation from the path never exceeds 30 cm. It clearly outperforms an industrial pure-pursuit controller in terms of path accuracy and a standard MPC in terms of driving smoothness. 

Place, publisher, year, edition, pages
IEEE, 2017. Vol. 2, no 4, p. 238-250
Keywords [en]
Autonomous vehicles, predictive control
National Category
Control Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-220573DOI: 10.1109/TIV.2017.2767279OAI: oai:DiVA.org:kth-220573DiVA, id: diva2:1169477
Projects
iQMatic
Funder
VINNOVA, 2012-04626
Note

QC 20180117

Available from: 2017-12-27 Created: 2017-12-27 Last updated: 2018-01-17Bibliographically approved

Open Access in DiVA

fulltext(12148 kB)58 downloads
File information
File name FULLTEXT01.pdfFile size 12148 kBChecksum SHA-512
a2260928b4c43798c192c67f36f237ab8e95322fc7072c0055679ce908c099c32e6b2ccaa1e06cb7cc1407ead04249d7d8f25cd82aed5bec42ad9c0374b7d824
Type fulltextMimetype application/pdf

Other links

Publisher's full texthttp://ieeexplore.ieee.org/document/8086190/

Search in DiVA

By author/editor
Lima, Pedro F.Mårtensson, JonasWahlberg, Bo
By organisation
Automatic ControlACCESS Linnaeus Centre
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 58 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 423 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