Joint Optimization for Pedestrian, Information and Energy Flows in Emergency Response Systems With Energy Harvesting and Energy Sharing

Bi, Huibo, Shang, Wen-Long, Chen, Yanyan and Wang, Kezhi (2022) Joint Optimization for Pedestrian, Information and Energy Flows in Emergency Response Systems With Energy Harvesting and Energy Sharing. IEEE Transactions on Intelligent Transportation Systems. pp. 1-15. ISSN 1524-9050 (In Press)

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Official URL: https://doi.org/10.1109/TITS.2022.3159503

Abstract

The rapid progress in informatisation and electrification in transportation has gradually transferred public transport junctions such as metro stations into the nexus of pedestrian flows, information flows, computation flows and energy flows. These smart environments that are efficient in handling large volume passenger flows in routine circumstances can become even more vulnerable during emergency situations and amplify the losses in lives and property owing to power outage triggered service degradation and destructive crowed behaviours. On the bright side, the increasingly abundant resources contained in smart environments have enlarged the optimisation space of an evacuation process, yet little research has concentrated on the joint optimal resource allocation between transportation infrastructures and pedestrians. Hence, in the paper, we propose a queueing network based resource allocation model to comprehensively optimise various types of resources during emergency evacuations. Experiments are conducted in a simulated metro station environment with realistic settings. The simulation results show that the proposed model can considerably improve the evacuation efficiency as well as the robustness of the emergency response system during emergency situations.

Item Type: Article
Additional Information: Funding information: This work was supported in part by the Beijing Natural Science Foundation Program under Grant 21L00097, in part by the International Research Cooperation Seed Fund of Beijing University of Technology under Grant 2021A04 and Grant 2021B14, and in part by the Postdoctoral Research Foundation of China under Grant 2021M690341.
Uncontrolled Keywords: Emergency management, energy harvesting, G-networks, resource allocation, transportation infrastructure system optimisation
Subjects: G400 Computer Science
H300 Mechanical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 30 May 2022 14:03
Last Modified: 30 May 2022 14:15
URI: http://nrl.northumbria.ac.uk/id/eprint/49217

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