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MacroServ: A Route Recommendation Service for Large-Scale Evacuations

Lookup NU author(s): Professor Raj Ranjan


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To respond to emergencies in a fast and an effective manner, it is of critical importance to have efficient evacuation plans that lead to minimum road congestions. Although emergency evacuation systems have been studied in the past, the existing approaches, mostly based on multi-objective optimizations, are not scalable enough when involve numerous time varying parameters, such as traffic volume, safety status, and weather conditions. In this paper, we propose a scalable emergency evacuation service, termed the MacroServ that recommends the evacuees with the most preferred routes towards safe locations during a disaster. Unlike many existing approaches that model systems with static network characteristics, our approach considers real-time road conditions to compute the maximum flow capacity of routes in the transportation network. The evacuees are directed towards those routes that are safe and have least congestion resulting in decreased evacuation time. We utilized probability distributions to model the real-life stochastic behaviors of evacuees during emergency scenarios. The results indicate that recommendation of appropriate routes during emergency scenarios play a critical role in quicker and safe evacuation of the population.

Publication metadata

Author(s): Khan MUS, Khalid O, Huang Y, Zhang F, Ranjan R, Khan SU, Cao J, Li K, Veeravalli B, Zomaya A

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Services Computing

Year: 2016

Issue: 99

Pages: 1-1

Online publication date: 05/11/2015

Acceptance date: 01/01/1900

ISSN (electronic): 1939-1374

Publisher: IEEE


DOI: 10.1109/TSC.2015.2497241


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