Cooperative weaving for connected and automated vehicles to reduce traffic oscillation

Yu Bai, Yu Zhang, Xin Li, Jia Hu*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)


In weaving areas, vehicles frequently carry out conflicting lane-changing manoeuvres. The frequent lane change in this area results in rapid changes in vehicles’ speed, which in turn reduces traffic efficiency and create traffic bottlenecks at weaving areas. This research proposes a cooperative weaving motion planner for connected and automated vehicles to reduce traffic oscillation. The proposed motion planner is based on model predictive control method and solved by Chang-Hu’s method. Paper presented at the Intelligent Transportation Systems (ITSC), 2018 IEEE). The motion planner only requires longitudinally automation which is accessible for most commercialized luxury vehicles. Simulation evaluation was conducted to quantify the performance of the proposed motion planner. The results show that the proposed motion planner is able to reduce traffic oscillation by 2.7% to 28.0%. Furthermore, the computation time of the proposed planner is fewer than 20 milliseconds indicating readiness to real-time application.

Original languageEnglish
Pages (from-to)125-143
Number of pages19
JournalTransportmetrica A: Transport Science
Issue number1
Publication statusPublished - 2019


  • 081801
  • connected and automated vehicles
  • cooperative automation
  • Cooperative weaving
  • model predictive control


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