A Micro-Simulation Study of the Generalized Proportional Allocation Traffic Signal Control

Research output: Contribution to journalArticle

Abstract

We study the problem of controlling phase activations for signalized junctions in an urban transportation network using local feedback information consisting of measures of the queue-lengths at the incoming lanes of each junction. Our focus is on the validation and performance evaluation through micro-simulations of the recently proposed Generalized Proportional Allocation (GPA) controller. Previous theoretical work has provided provable performance guarantees in terms of stability, and throughput optimality of the GPA controller in a continuous averaged dynamical queueing network model. In this paper, we first provide and implement two discretized versions of the GPA controller in the SUMO micro simulator. We then compare, in an artificial Manhattan-like grid, the performance of the GPA controller with those of the MaxPressure controller, which is another distributed feedback controller that requires more information than the GPA. Finally, to show that the GPA controller is easily implementable in a real-world scenario, we apply it to a previously published realistic traffic scenario for the city of Luxembourg and compare its performance with the static controller provided with the scenario as well as with the cyclic MaxPressure controller. The simulations show that the GPA controller outperforms both the fixed time and the cyclic MaxPressure controllers for the Luxembourg scenario, and behaves better than the MaxPressure pressure controller in the Manhattan-grid when the demands are low.

Details

Authors
Organisations
External organisations
  • Polytechnic University of Turin
  • Georgia Institute of Technology
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering

Keywords

  • Decentralized traffic signal control, microscopic traffic simulation
Original languageEnglish
Article number8931730
Pages (from-to)1705-1715
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number4
Publication statusPublished - 2020
Publication categoryResearch
Peer-reviewedYes