A dynamic scalable scheme for managing mixed crowds

Najah A. Abuali, Abd Elhamid M. Taha

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


    Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process Scheme MDP to realize a smart infrastructure that is directly aimed at crowd management. A key emphasis of the scheme is a robust and reliable scalability that provides sufficient flexibility to manage a mixed crowd (i.e., pedestrian, cyclers, manned vehicles and unmanned vehicles). The infrastructure also spans various population settings (e.g., roads, buildings, game arenas, etc.). To realize a reliable and scalable crowd management scheme, the classical MDP is decomposed into Local MDPs with smaller action-state spaces. Preliminarily results show that the MDP decomposition can reduce the system global cost and facilitate fast convergence to local near-optimal solution for each L-MDP.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Communications, ICC 2017
    EditorsMerouane Debbah, David Gesbert, Abdelhamid Mellouk
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781467389990
    Publication statusPublished - Jul 28 2017
    Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
    Duration: May 21 2017May 25 2017

    Publication series

    NameIEEE International Conference on Communications
    ISSN (Print)1550-3607


    Other2017 IEEE International Conference on Communications, ICC 2017

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering


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