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Network Traffic Signal Control with Short-Term Origin-Destination Demand in a Connected Vehicle Environment via Mobile Edge Computing

  • Author / Creator
    Zhang, Can
  • This thesis develops and analyzes centralized and decentralized network-level traffic signal control system under in a connected vehicle (CV) environment with mobile edge computing (MEC). The goal is to provide a framework of decentralized signal control (DSC) system especially for real-time control and large-scale traffic network. Short-term origin-destination (OD) demand is used as an input given that the technological paradigm assumed is within the CV environment, unlike most previous works that look at network control but in a current technological paradigm. Considering short-term OD demand as inputs, a queue-based dynamic traffic assignment (DTA) model is proposed to predict traffic dynamics in traffic networks with signal control. Although DTA has been an effective tool to describe traffic dynamics for traffic optimization, and many researchers have considered traffic signal control in their models, signal timings have been simplified without considering complex, but realistic, phase sequence and duration restrictions. This work formulates traffic signal timing as a component of the link performance function with three control variables: cycle length, phase split, and offset. In addition, both user-optimal (UO) and system-optimal (SO) DTA problems are solved within a single corridor network. Finally, this thesis provides a simulation-based framework of both centralized and decentralized signal control to solve the network-level traffic signal control optimization problem. For the centralized system, this work solves the issue of optimal control using a three-step naïve method. Because the optimization of large-scale network traffic signals is a Nondeterministic Polynomial Time (NP)-complete problem, the centralized system is further decomposed into a decentralized system where the network is divided into subnetworks. – Each subnetwork has its own agent that optimizes signals within the subnetwork. The proposed control systems are applied to a set of test scenarios constructed using different demand levels in different grid networks. This work also investigates the impact of network decomposition strategy on the signal control system performance. Results show that network decomposition with smaller subnetworks results in less Computational Time (CT), but also increased Average Travel Time (ATT) and Total Travel Delay (TTD). This thesis contributes to the literature by a queue-based DTA model for traffic network with real traffic signal timing plan, a simulation-based framework of DSC system within the MEC-enabled CV environment, and a scalable and extendable decomposition method for a DSC system.

  • Subjects / Keywords
  • Graduation date
    Fall 2021
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/r3-m5fw-a389
  • 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.