TRAPPed in traffic? A self-adaptive framework for decentralized traffic optimization

Ilias Gerostathopoulos, Evangelos Pournaras

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Optimizing the traffic flow in a city is a challenging problem, especially in a future traffic system of self-driving cars and sharing vehicles. This is due to the interactions between the individual traffic agents (vehicles) that compete for the use of the common infrastructure (streets) given traffic dynamics such as stop-and-go effects, changing lanes, and other. The goal of this paper is to provide a solution to the above problem that works in a fully decentralized and participatory way, i.e. autonomous agents collaborate without a centralized data collector and arbitrator. Such a solution should be scalable, privacy-preserving, and flexible with respect to the degree of autonomy of agents. A self-adaptive framework to support this research is introduced: TRAPP - Traffic Reconfigurations via Adaptive Participatory Planning. The framework relies on a microscopic traffic simulator, SUMO, for simulating urban mobility scenarios, and on a decentralized multi-agent planning system, EPOS, for decentralized combinatorial optimization, applied here in traffic flows. A data-driven interoperation of the two tools in the proposed framework allows high modularity and customization for experimenting with different scenarios, optimization objectives and agents' behavior and as such providing new perspectives for resilient future traffic infrastructures.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2019
PublisherIEEE Computer Society
Pages32-38
Number of pages7
ISBN (Electronic)9781728133683
DOIs
Publication statusPublished - 1 May 2019
Externally publishedYes
Event14th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2019 - Montreal, Canada
Duration: 25 May 201926 May 2019

Publication series

NameICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems
Volume2019-May
ISSN (Print)2157-2305
ISSN (Electronic)2156-7891

Conference

Conference14th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2019
CountryCanada
CityMontreal
Period25/05/1926/05/19

Keywords

  • framework
  • multi-agent system
  • optimization
  • planning
  • self-adaptation
  • traffic

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  • Cite this

    Gerostathopoulos, I., & Pournaras, E. (2019). TRAPPed in traffic? A self-adaptive framework for decentralized traffic optimization. In Proceedings - 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2019 (pp. 32-38). [8787057] (ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems; Vol. 2019-May). IEEE Computer Society. https://doi.org/10.1109/SEAMS.2019.00014