Cooperative Decision Making of Lane-change for Automated Vehicles Considering Human-like Driving Characteristics

Peng Hang, Chen Lv, Chao Huang, Zhongxu Hu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


To deal with the cooperative lane-change decision-making issue of autonomous vehicles (AVs), a cooperative coalitional game approach is utilized considering human-like driving characteristics. Firstly, three different driving characteristics are defined for AVs, i.e., aggressive, moderative and conservative. Then, the single-track vehicle model is applied to the system modeling for lane-change decision making. Moreover, the cost function of decision making is constructed considering three vital performance indexes, i.e., safety, comfort and efficiency. Furthermore, the cooperative lane-change decision-making issue is transformed into an optimization problem with multi-constraints via the cooperative coalitional game approach. Finally, testing cases are carried out to verify the feasibility and effectiveness of the proposed approach. Testing results indicate that the designed algorithm is able to make safe and correct lane-change decisions for AVs. Additionally, it can adapt to different driving characteristics of AVs.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9789881563804
Publication statusPublished - 26 Jul 2021
Externally publishedYes
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927


Conference40th Chinese Control Conference, CCC 2021


  • autonomous vehicle
  • Decision making
  • driving characteristic
  • game theory
  • human-like
  • lane change

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation

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