An integrative behavioral-based physics-inspired approach to traffic congestion control

Hossein Rastgoftar, Jean Baptiste Jeannin, Ella Atkins

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

1 Scopus citations

Abstract

This paper offers an integrative behavioral-based physics-inspired approach to model and control traffic congestion in an efficient manner. While existing physics-based approaches commonly assign density and traffic flow states with the Fundamental Diagram, this paper specifies the flow-density relation using past traffic behavior (intent) recorded over a time sliding window with constant horizon length. With this approach, traffic coordination trends can be consistently learned and incorporated into traffic planning. This is integrated with mass conservation law (continuity) to model traffic coordination as a probabilistic process and obtain traffic feasibility conditions using linear temporal logic. By spatial discretization of a network of interconnected roads (NOIR), the NOIR is represented by a graph with inlet boundary nodes, outlet boundary nodes, and interior nodes. The paper offers a boundary control approach to manage congestion through the inlet boundary nodes. More specifically, model predictive control (MPC) is applied to control traffic congestion through the boundary of the traffic network. Therefore, the optimal boundary inflow is assigned as the solution of a constrained quadratic programming problem with equality and inequality constrained. The simulation results shows that the proposed MPC boundary controller can successfully control the traffic through the inlet boundary nodes where traffic reaches the steady state condition.

Original languageEnglish (US)
Title of host publicationIntelligent Transportation/Vehicles; Manufacturing; Mechatronics; Engine/After-Treatment Systems; Soft Actuators/Manipulators; Modeling/Validation; Motion/Vibration Control Applications; Multi-Agent/Networked Systems; Path Planning/Motion Control; Renewable/Smart Energy Systems; Security/Privacy of Cyber-Physical Systems; Sensors/Actuators; Tracking Control Systems; Unmanned Ground/Aerial Vehicles; Vehicle Dynamics, Estimation, Control; Vibration/Control Systems; Vibrations
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791884287
DOIs
StatePublished - 2020
Externally publishedYes
EventASME 2020 Dynamic Systems and Control Conference, DSCC 2020 - Virtual, Online
Duration: Oct 5 2020Oct 7 2020

Publication series

NameASME 2020 Dynamic Systems and Control Conference, DSCC 2020
Volume2

Conference

ConferenceASME 2020 Dynamic Systems and Control Conference, DSCC 2020
CityVirtual, Online
Period10/5/2010/7/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Automotive Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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