Partition-based parametric active model discrimination with applications to driver intention estimation

Ruochen Niu, Qiang Shen, Sze Yong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a partition-based parametric active model discrimination approach that distinguishes among a set of discrete-time affine time-invariant models with uncontrolled inputs, model-independent parameters that are revealed in real-time and noise. By partitioning the operating region of the parameters, the problem turns into a sequence of offline optimization problems. Thus, at each time instant, we only need to determine which subregion in the resulting partition tree the revealed parameters lie in and select the corresponding pre-computed inputs. The offline optimal input design problem is formulated as a bilevel problem and further cast as a mixed-integer linear program (MILP). Finally, we demonstrate the effectiveness of the proposed approach for estimating driver intention in a lane-changing scenario.

Original languageEnglish (US)
Title of host publication2019 18th European Control Conference, ECC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3880-3885
Number of pages6
ISBN (Electronic)9783907144008
DOIs
StatePublished - Jun 1 2019
Event18th European Control Conference, ECC 2019 - Naples, Italy
Duration: Jun 25 2019Jun 28 2019

Publication series

Name2019 18th European Control Conference, ECC 2019

Conference

Conference18th European Control Conference, ECC 2019
CountryItaly
CityNaples
Period6/25/196/28/19

ASJC Scopus subject areas

  • Instrumentation
  • Control and Optimization

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  • Cite this

    Niu, R., Shen, Q., & Yong, S. (2019). Partition-based parametric active model discrimination with applications to driver intention estimation. In 2019 18th European Control Conference, ECC 2019 (pp. 3880-3885). [8795825] (2019 18th European Control Conference, ECC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ECC.2019.8795825