Visible to the public A dynamic scalable scheme for managing mixed crowds

TitleA dynamic scalable scheme for managing mixed crowds
Publication TypeConference Paper
Year of Publication2017
AuthorsAbuAli, N. A., Taha, A. E. M.
Conference Name2017 IEEE International Conference on Communications (ICC)
PublisherIEEE
ISBN Number978-1-4673-8999-0
KeywordsAutomated Response Actions, Buildings, composability, crowd safety, dynamic scalable scheme, emergency management, Markov decision process scheme, Markov processes, MDP decomposition, mixed crowd management, prompt emergency response, pubcrawl, Real-time Systems, Resiliency, Roads, Safety, Sensors, smart infrastructure, smart phones, smartphones, social networking (online), social networks, spontaneous alerts, spontaneous notifications, traffic engineering computing, traffic management context, Urban areas
Abstract

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.

URLhttps://ieeexplore.ieee.org/document/7997264
DOI10.1109/ICC.2017.7997264
Citation Keyabuali_dynamic_2017