Modelling elevator traffic with social distancing in a university classroom building

Abstract

Social distancing standards implemented during the COVID-19 pandemic may have negative effects on vertical traffic. We describe a model and use it to predict the elevator traffic under social distancing in a university classroom building, and study the effects of four interventions aimed at improving this traffic. Discrete event-based simulation is used to study whether the lift group meets the forecasted demand when the car capacity is restricted far below its ordinary value to accommodate social distancing. Four low-cost interventions are simulated alone and in combination to quantify the improvements they offer. All four interventions show some improvement, and the combination of all four interventions gives the greatest improvement. Practical application: Implementing social distancing standards may disproportionately lower the car capacity relative to the building population and thus negatively affect vertical traffic. Building managers seeking to implement low-cost measures to improve elevator traffic under these conditions may look to the percentage improvements described here to aid them in selecting interventions appropriate to their buildings.

A review of facilities management interventions to mitigate respiratory infections in existing buildings

“…Six articles considered occupancy density as a variable in their models assessing the effectiveness of IAQ interventions [ 60 , 62 , 70 , 72 , 76 , 77 ]. Moreover, nine studies assessed the effectiveness of space management and occupancy control in various settings such as schools [ 129 , [132] , [133] , [134] , [135] ], hospitals [ 131 ], clubhouses [ 56 ], and offices [ 28 ].…”

“…What is more, Bogdan-Petru et al presented a system equipped with IoT that would enable office users to handle office items remotely without touching them, such as opening and closing the entry door, controlling lighting, and operating the coffee machine [ 155 ]. Additionally, Swinarski et al simulated occupants’ behaviours in an educational building to evaluate the four different interventions for elevator operation [ 135 ]. Likewise, Makhsous et al demonstrated that a real-time aerosol sensor network could properly assess aerosol transmission in medical settings, providing information to assist intervention decision-making [ 51 ].…”

Queuing safely for elevator systems amidst a pandemic

“…COVID-19 pandemic (Swinarski, 2021) models and predicts elevator traffic in a university classroom building when passengers mainly travel in the predetermined short time periods between two classes, with known class schedules and traffic patterns. The authors discuss an intervention that directs passengers to sort themselves into pairs of passengers with a shared destination floor, which can improve the performance, but is not as effective as moving classes to lower floors or staggering course start times.…”

“…The COVID‐19 pandemic has made it imperative to design interventions for people to stay safe in potentially crowded areas. For high‐rise buildings, social distancing reduces the capacity of elevators, cutting the number of passengers per elevator by two‐thirds or as much as over $$90\%$$ of the normal amount (Swinarski, 2020, 2021; Weber, 2020). Reduced elevator capacity can cause large lobby queues and long wait times, resulting in crowding and reduced social distancing (Smith, 2020; van Rijn et al., 2020; Weber, 2020; Wilson, 2020).…”

Queuing Safely for Elevator Systems Amidst a Pandemic

“…The COVID-19 pandemic has made it imperative to design interventions for people to stay safe in potentially crowded areas. For high-rise buildings, social distancing reduces the capacity of elevators, cutting the number of passengers per elevator by two-thirds or as much as over 90% of the normal amount (Swinarski, 2020(Swinarski, , 2021Weber, 2020). Reduced elevator capacity can cause large lobby queues and long wait times, resulting in crowding and reduced social distancing (Smith, 2020; van Rijn et al, 2020;Weber, 2020;Wilson, 2020).…”