Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Optimal Input Design for Affine Model Discrimination with Applications in Intention-Aware Vehicles
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
Show others and affiliations
2018 (English)In: Proceedings - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 297-307Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the optimal design of input signals for the purpose of discriminating among a finite number of affine models with uncontrolled inputs and noise. Each affine model represents a different system operating mode, corresponding to unobserved intents of other drivers or robots, or to fault types or attack strategies, etc. The input design problem aims to find optimal separating/discriminating (controlled) inputs such that the output trajectories of all the affine models are guaranteed to be distinguishable from each other, despite uncertainty in the initial condition and uncontrolled inputs as well as the presence of process and measurement noise. We propose a novel formulation to solve this problem, with an emphasis on guarantees for model discrimination and optimality, in contrast to a previously proposed conservative formulation using robust optimization. This new formulation can be recast as a bilevel optimization problem and further reformulated as a mixed-integer linear program (MILP). Moreover, our fairly general problem setting allows the incorporation of objectives and/or responsibilities among rational agents. For instance, each driver has to obey traffic rules, while simultaneously optimizing for safety, comfort and energy efficiency. Finally, we demonstrate the effectiveness of our approach for identifying the intention of other vehicles in several driving scenarios.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. p. 297-307
Keywords [en]
Autonomous driving, Input design, Intention identification, Model discrimination, Embedded systems, Energy efficiency, Integer programming, Machine design, Uncertainty analysis, Bi-level optimization problems, Initial conditions, Mixed integer linear program, Optimal input design, Robust optimization, Problem solving
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-238008DOI: 10.1109/ICCPS.2018.00036Scopus ID: 2-s2.0-85046048037ISBN: 9781538653012 (print)OAI: oai:DiVA.org:kth-238008DiVA, id: diva2:1278940
Conference
9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018, 11 April 2018 through 13 April 2018
Note

Conference code: 138985; Export Date: 30 October 2018; Conference Paper; Funding details: TPCRI, Toyota Physical and Chemical Research Institute; Funding details: N66001-14-1-4045, DARPA, Defense Advanced Research Projects Agency; Funding text: This work was supported by an Early Career Faculty grant from NASA’s Space Technology Research Grants Program, DARPA grant N66001-14-1-4045 and by Toyota Research Institute (“TRI”). TRI provided funds to assist the authors with their research but this article solely reflects the opinions and conclusions of its authors and not TRI or any other Toyota entity.

QC 20190115

Available from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-01-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Jacobsen, Emil

Search in DiVA

By author/editor
Jacobsen, Emil
By organisation
Mathematics (Dept.)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 3 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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