A field study and analysis of passengers arriving at lift lobbies in social groups in multi-storey office, hotel and residential buildings

Abstract

This field study was made to study the size of social groups among passengers travelling with lifts. The group size was observed in three types of buildings located in four countries, totally in nine multi-storey buildings. The observations were carried out manually for 12 hours on a normal weekday. Analysis results show that the daily mean group size was generally low: 1.2–1.3 persons in the offices, 1.3–2.0 persons in the hotels and 1.1–1.4 persons in the residential buildings. Hourly means differed significantly from the daily means for each building. This suggests that group size should be considered on hourly or shorter basis. In addition, goodness-of-fit tests were conducted to determine a statistical model for the group size. A geometric distribution was found to fit the data the best across all building types which simplifies modeling of passenger group arrivals in buildings. Practical application: This article contributes to the understanding of lift passenger tendency to travel in socially connected groups in multi-storey buildings. A unique data set of group size observations around the world is reported on an hourly basis for office, hotel and residential buildings. A geometric distribution is proposed to model the group size statistically, which simplifies the use of socially connected groups when generating passengers in lift traffic simulations. The real-world data and the statistical model of the group size enable more realistic lift traffic simulations that are routinely conducted during the design phase of multi-storey buildings.

In-depth Study on RTT-HC-MTT Relationship for Passenger Demand beyond Elevator Contract Capacity by Simulation

“…For (i), it has already been confirmed [10][11][12][13] that uppeak traffic is no longer the dominant traffic pattern in a modern office building. Furthermore, the lunch peak mainly consisting of mixed traffic patterns may be even worse, which is considered the main challenge to an elevator system [14][15][16]. It is customary nowadays to quantitatively describe the prevailing traffic in a modern high-rise building at any time as a mixture of simultaneous incoming, outgoing and interfloor traffic demands [3].…”

Universal elevator round trip time calculation for general traffic conditions with extension to batch arrivals

“…To show how realistic this method is, the group size distribution as surveyed in a hotel in Singapore is used 17 (Sorsa et al 2020), approximately based on Figure 4 in that article. Here, G = 5, g (1) = 48%, g (2) = 30%, g (3) = 12%, g (4) = 7%, g (5) = 3%, GS = 1.87, NoB = 8.56.…”

“…Then, the expected number of down-stops is a sum of all probabilities that the i th floor is a potential stop of down-journeys, i from 1 to B+N, as given by equation (17).…”

“…The latest study was performed at three types of buildings, totally nine number, in four countries, namely Finland, Singapore, United Arab Emirates, and The United States of America 17 (Sorsa et al 2020). The survey was done manually over a period of 12 hours on a normal weekday.…”