Automated driving lane change algorithm based on robust model predictive control for merge situations on highway intersections

Heongseok Chae, Yonghwan Jeong, Kyongchan Min, Myungsu Lee, Kyongsu Yi

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.

Original languageEnglish
Pages (from-to)575-583
Number of pages9
JournalTransactions of the Korean Society of Mechanical Engineers, A
Volume41
Issue number7
DOIs
StatePublished - Jul 2017

Keywords

  • Automated Driving Control Algorithm
  • Highway Automated Driving
  • Merge Mode Decision
  • Merge Situation on Highway
  • Model Predictive Control
  • Safe Driving Envelope Decision

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