A Game Theoretic Model Predictive Controller With Aggressiveness Estimation for Mandatory Lane Change

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dc.authoridLangari, Reza/0000-0001-7900-5186
dc.authoridCoskun, Serdar/0000-0002-7080-0340
dc.contributor.authorZhang, Qingyu
dc.contributor.authorLangari, Reza
dc.contributor.authorTseng, H. Eric
dc.contributor.authorFilev, Dimitar
dc.contributor.authorSzwabowski, Steven
dc.contributor.authorCoskun, Serdar
dc.date.accessioned2025-03-17T12:25:38Z
dc.date.available2025-03-17T12:25:38Z
dc.date.issued2020
dc.departmentTarsus Üniversitesi
dc.description.abstractIn this article, we develop a game theoretic model predictive controller (GTMPC) with aggressiveness estimation to deal with the mandatory lane change (MLC) problem in presence of several surrounding vehicles. GTMPC is responsible for driving a subject vehicle (SV) to a desired longitudinal position and executing lane-changing at the optimal moment. Specifically, GTMPC constantly establishes and solves Stackelberg games corresponding to multiple game candidate vehicles (GCV) within the game scope when SV is able to interact with GCVs by signaling a lane change intention through turn signal. GTMPC first selects one target vehicle (TV) within multiple GCVs based on the Stackelberg equilibrium, followed by estimating TV's aggressiveness based on the interaction between SV and TV, then completes the maneuver through MPC. GTMPC performance is compared with level-k game theoretic controller. Human-in-the-Loop results showed that GTMPC is capable to safely complete the MLC by properly assessing the aggressiveness of surrounding vehicles, driven either by intelligent driver model or human drivers.
dc.description.sponsorshipFord Motor Company [URP 2016-8009R]
dc.description.sponsorshipThis work was supported by Ford Motor Company (URP 2016-8009R).
dc.identifier.doi10.1109/TIV.2019.2955367
dc.identifier.endpage89
dc.identifier.issn2379-8858
dc.identifier.issn2379-8904
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85082633712
dc.identifier.scopusqualityQ1
dc.identifier.startpage75
dc.identifier.urihttps://doi.org/10.1109/TIV.2019.2955367
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1789
dc.identifier.volume5
dc.identifier.wosWOS:000722586600007
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeee-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Transactions On Intelligent Vehicles
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectGame theory
dc.subjectautonomous driving
dc.subjectdriver aggressiveness
dc.titleA Game Theoretic Model Predictive Controller With Aggressiveness Estimation for Mandatory Lane Change
dc.typeArticle

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