Combined Control of Freeway Traffic Involving Cooperative Adaptive Cruise Controlled and Human Driven Vehicles Using Feedback Control Through SUMO


Silgu M. A. , Erdağı İ. G. , Göksu G. , Çelikoğlu H. B.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Doi Number: 10.1109/tits.2021.3098640
  • Title of Journal : IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
  • Keywords: Traffic control, ITU, Tools, State feedback, Roads, Symmetric matrices, Safety, Control theory, road traffic control, state feedback, robust control, autonomous vehicles, connected vehicles, cruise control, simulation, MODEL-PREDICTIVE CONTROL, VARIABLE-SPEED LIMIT, END COLLISION RISKS, INTEGRATED CONTROL, RAMP CONTROL, FLOW, IMPACTS, BOTTLENECKS, AUTOMATION, STABILITY

Abstract

In this study, we propose and test through micro-simulation a novel controller for the combined control of freeway traffic by adopting coordinated Ramp Metering (RM) and Variable Speed Limiting (VSL) strategies. In order to figure out the performance of the $H_{infinity}$ State Feedback Controller we have designed, field observations on a real freeway segment with four on-ramps and an off-ramp in the city of Istanbul are used to calibrate the Intelligent Driver Model at SUMO (Simulation of Urban MObility). Scenarios with varying penetration rates of vehicles with Cooperative Adaptive Cruise Control (CACC) in mixed traffic are simulated through SUMO specific to the cases of no control, only coordinated RM control, and the combined coordinated RM + VSL control. Performance of the controller we have proposed has been analyzed considering a number of measures on traffic flow dynamics and emissions exhausted. We define three critical levels for penetration rates of vehicles with CACC in freeway traffic.