Boundary Control of Traffic Congestion Modeled as a Non-stationary Stochastic Process

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we introduce a new conservation-based approach to model traffic dynamics, and apply the model predictive control (MPC) approach to manage the boundary traffic inflow and outflow, so that the traffic congestion is reduced. We establish an interface between the Simulation of Urban Mobility (SUMO) software and MATLAB to define a network of interconnected roads (NOIR) as a directed graph, and present traffic congestion management as a network control problem. By formally specifying the traffic feasibility conditions, and using the linear temporal logic, we present the proposed MPC-based boundary control problem as a quadratic programming with linear equality and inequality constraints. The success of the proposed traffic boundary control is demonstrated by simulation of traffic congestion control in Center City Philadelphia.

Original languageEnglish (US)
Title of host publication2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages455-461
Number of pages7
ISBN (Electronic)9781665476874
DOIs
StatePublished - 2022
Event17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022 - Singapore, Singapore
Duration: Dec 11 2022Dec 13 2022

Publication series

Name2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022

Conference

Conference17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022
Country/TerritorySingapore
CitySingapore
Period12/11/2212/13/22

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Modeling and Simulation

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