Coordination Strategies of Connected and Automated Vehicles near On-ramp Bottlenecks on Motorways

N. Chen

Research output: ThesisDissertation (TU Delft)

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The aim of the thesis is to design coordination strategies for connected automated vehicles near on-ramps considering controller performance, safe lane changing conditions, maneuver planning, and trajectory control. CAVs have enhanced situation awareness with their onboard detection units and vehicle-to-everything communications. They have the potential to improve traffic operations by manoeuvring together under a common goal and by accepting a small time gap. Existing model predictive control controllers rarely check their controllers’ robustness considering the mismatch between vehicle dynamics and prediction models. The existing cooperative merging strategies constrain that on-ramp CAVs merge into mainline traffic after reaching the final desired inter-vehicle distance and/or (merging) speed. That constraint may make them not be applied to scenarios where the length of the on-ramp lane is short and on-ramp CAVs cannot reach desired states before merging. Few methods investigate optimal merging sequences for two conflicting streams of traffic. Besides, mainline CAVs are rarely allowed to change lane during cooperation. This thesis consecutively tackles the aforementioned four points by presenting four coordination strategies that address the mentioned limitations...
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • van Arem, B., Supervisor
  • Wang, M., Advisor
Thesis sponsors
Award date22 Dec 2021
Print ISBNs978-90-5584-304-6
Publication statusPublished - 2021

Bibliographical note

TRAIL Thesis Series no. T2021/29, the Netherlands TRAIL Research School


  • Connected automated vehicles (CAVs)
  • Trajectory planning
  • Maneuvering control
  • on-ramp merging
  • Hierarchical control


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