Trajectory Planning for Connected and Automated Vehicles: Cruising, Lane Changing, and Platooning

Xiangguo Liu, Guangchen Zhao, Neda Masoud, Qi Zhu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Autonomy and connectivity are considered among the most promising technologies to improve safety and mobility and reduce fuel consumption and travel delay in transportation systems. In this paper, we devise an optimal control-based trajectory planning model that can provide safe and efficient trajectories for the subject vehicle while incorporating platoon formation and lane-changing decisions. We embed this trajectory planning model in a simulation framework to quantify its fuel efficiency and travel time reduction benefits for the subject vehicle in a dynamic traffic environment. Specifically, we compare and analyze the statistical performance of different controller designs in which lane changing or platooning may be enabled, under different values of time (VoTs) for travelers. Results from extensive numerical experiments indicate that our design can not only provide first-hand cost savings for the subject vehicle but also second-hand savings for vehicles upstream of the subject vehicle. Experiments also highlight that lane changing and platooning can both offer benefits, depending on the relative values of fuel cost and the traveler's VoT: with a small VoT, the fuel efficiency benefits of platooning outweigh time savings offered by lane changing. However, a vehicle with a high VoT may find it more beneficial to travel outside of a platoon and complete its trip faster by leveraging lane changes.

Original languageEnglish (US)
JournalSAE International Journal of Connected and Automated Vehicles
Issue number4
StatePublished - Oct 22 2021


  • Connected and automated vehicles
  • Lane changing
  • Platooning
  • Trajectory planning

ASJC Scopus subject areas

  • Automotive Engineering
  • Computer Science Applications
  • Artificial Intelligence
  • Control and Systems Engineering


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