MILE: Multiobjective Integrated Model Predictive Adaptive Cruise Control for Intelligent Vehicle

Yu Zhang, Mingfan Xu, Yechen Qin*, Mingming Dong, Li Gao, Ehsan Hashemi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

Adaptive cruise control (ACC) systems currently face the challenge of balancing tracking performance and avoiding collisions with arbitrary cut-in vehicles from different lanes. The multiobjective ACC proposed in this article is based on a novel integrated structure. The novel integrated ACC structure consists of an adaptive controller and the associated switching mechanism. The controller combines the upper and lower layers, which are common in today's hierarchical controllers. The switching mechanism is designed to switch between different modes to avoid collisions and maintain tracking capability in complex driving scenarios. Complex scenarios are designed to validate the integrated structure's effectiveness, real-time performance, and robustness, and a driver-in-the-loop platform is established. The results indicate that the novel integrated structure is capable of tracking the preceding vehicle accurately while avoiding colliding with the surrounding vehicle from various directions, thereby ensuring vehicle stability under varying road adhesion and system uncertainties.

Original languageEnglish
Pages (from-to)8539-8548
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume19
Issue number7
DOIs
Publication statusPublished - 1 Jul 2023

Keywords

  • Adaptive cruise control (ACC)
  • crash avoidance (CA)
  • driver-in-the-loop (DiL) test
  • speedgoat

Fingerprint

Dive into the research topics of 'MILE: Multiobjective Integrated Model Predictive Adaptive Cruise Control for Intelligent Vehicle'. Together they form a unique fingerprint.

Cite this