Adaptive Signal Control and Coordination in Connected Vehicle Environment

• Author / Creator

  Jiangchen Li

• Existing signal control systems are usually based on traffic flow data from fixed location detectors. Because of rapid advances in the emerging vehicular communication, connected vehicle (CV)-based signal control demonstrates significant improvements over existing conventional signal control systems. Though various CV-based signal control systems have been investigated in the past few years, these approaches still have issues to overcome. These issues include sub-optimal results in low market penetration conditions, underperformance in both under-saturated and saturated traffic conditions, a lack of consideration for rapidly changing demand uncertainties, and expensive complex signal control systems architecture.
  With this in mind, this thesis contributes to current research from three essential perspectives, including data, traffic model, and control strategy. More specifically, the contributions can be defined in the following ways: firstly, the issue of data quality is addressed with a proposed enhanced dynamic segmentation approach for the low penetration rate to obtain accurate traffic data; secondly, the traffic model is addressed by proposing a virtual cycle-based store and forward model (Vi-SFM) in addition to a dynamic parametric dispersion model for intersection and corridor level modeling, respectively; thirdly, the control strategy is addressed by proposing a model predictive control (MPC)-based framework for adaptive signal control and coordination, as well as a stability method, for a considerable scalable capability and good performance; finally, CV-centric in-the-loop testing prototypes for adaptive signal control and coordination are implemented.
  Both field and simulation results from implemented CV-centric in-the-loop testing then validate the efficiency of these proposed methods in the CV environment, in which the proposed methods have shorter travel times for different approaches, different demands, and different penetration rates than typical existing conventional signal control methods. In addition, both semi-closed loop control in 23 Ave. and closed-loop control in the South Campus are more efficient with lower travel times than non-CV-based open-loop control. Besides, simulation results of the proposed stable method indicate that high-frequency communication helps the MPC controller be more efficient with a faster convergency speed.

• Subjects / Keywords

  • Connected Vehicle
  • Adaptive Signal Control
  • Signal Coordination

• Graduation date

  Spring 2021

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-9ms4-3206

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.