A motion planner enabling cooperative lane changing: Reducing congestion under partially connected and automated environment

Yu Bai, Yu Zhang, Jia Hu

Research output: Contribution to journalArticleScientificpeer-review

Abstract

A cooperative lane-changing (CLC) motion planning algorithm for partially connected and automated environment is proposed in this study. Unlike conventional motion planner whose goal is merely enabling driving maneuver, this proposed algorithm takes one step further in terms of reducing oscillation and shockwave caused by lane change, hence improves transport mobility. The proposed motion planner is designed as a model predictive control which is solved by a dynamic programming-based numerical solution method. Since longitudinal automation is much more accessible than lateral automation, the motion planner requires only longitudinal automation in order to keep the design practical. The proposed motion planner is evaluated against the human driver. Sensitivity analysis is conducted in terms of the initial headway of the receiving gap. The results demonstrate that the motion planner reduces oscillation by 0.1%−9.4%. The variation is due to the changes in initial headway of receiving gap. The computation time is around 17-21 milliseconds showing great potential to be applied in real time.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalJournal of Intelligent Transportation Systems: technology, planning, and operations
DOIs
Publication statusE-pub ahead of print - 2020

Keywords

  • Connected and automated vehicle
  • cooperative lane change
  • model predictive control
  • traffic oscillation

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