Lift traffic analysis: Formulae for the general case

Peters, Richard

doi:10.1177/014362449001100204

Cited by 16 publications

(16 citation statements)

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“…The driving force behind the calculations and simulations as well as real elevators is the passenger arrival process which defines when and at which floors passengers arrive to register pickup requests, and what their destinations are. The theoretical calculations are based on queuing theory, and they can be used to study the performance of conventional elevator groups in up peak traffic conditions (Roschier and Kaakinen 1979, Peters 1990, Barney 2003, Al-Sharif 2010, Al-Sharif et al 2014. Other traffic situations and elevator systems based on destination control require simulation.…”

Section: Theoretical Foundationmentioning

confidence: 99%

The Elevator Trip Origin-Destination Matrix Estimation Problem

Kuusinen¹,

Sorsa²,

Siikonen³

2015

Transportation Science

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This dissertation studies people flow in buildings, especially the process of how passengers arrive at elevator lobbies, estimation of elevator passenger traffic, and human behaviour and decision making in evacuations. The arrival process is studied by taking into account, for the first time, that passengers do not always arrive and use elevators individually but rather in batches. The results suggest that the common assumption that individual arrivals follow a Poisson distribution may not hold when the proportion of batch arrivals is large.To estimate the elevator passenger traffic in a building, new mathematical models and algorithms are developed. The new methods are based on mathematical optimization, namely, linear programming, integer least squares and constraint programming. The results from numerical experiments show that the new approaches satisfy real-time elevator control requirements. In addition, randomized algorithms result in better quality passenger traffic statistics than traditional deterministic algorithms. The dissertation presents also an experimental evacuation study. The results show that people may not be able to select the fastest exit route and that cooperation may slow down the evacuation.The new estimation models and algorithms presented in this dissertation enable better elevator control and some of them are already being implemented by KONE Corporation. The results also give new insights into the process of how passengers arrive at the elevator lobbies and use elevators and into human behaviour in evacuation situations, which affect elevator and building safety planning. Tiivistelmä Tässä väitöskirjassa tutkitaan rakennusten henkilöliikennettä, erityisesti henkilöiden saapumisprosessia hissiauloihin, hisseillä tapahtuvan henkilöliikenteen estimointia sekä henkilöiden käyttäytymistä ja päätöksentekoa rakennuksen evakuoinnissa. Saapumisprosessia tutkitaan ottaen ensimmäistä kertaa huomioon, että henkilöt eivät aina saavu ja käytä hissiä yksin vaan isommissa joukoissa. Tulokset osoittavat, että yleinen olettamus yksittäisten saapumisten Poisson jakautuneisuudesta ei välttämättä päde, kun joukkosaapumisten osuus on suuri.Rakennuksen henkilöliikenteen estimoimiseksi väitöskirjassa kehitetään matemaattisia malleja ja algoritmeja, jotka perustuvat lineaariseen optimointiin, pienimmän neliösumman kokonaislukuoptimointiin ja rajoiteoptimointiin. Numeeristen testien tulokset osoittavat, että menetelmät toteuttavat todellisen hissiohjauksen reaaliaikavaatimukset. Lisäksi satunnaistetut algoritmit tuottavat laadultaan parempia henkilöliikennetilastoja kuin perinteiset deterministiset algoritmit. Väitöskirjassa esitetään myös kokeellinen evakuointitutkimus, jonka tulokset osoittavat, että ihmiset eivät välttämättä kykene valitsemaan nopeinta poistumisreittiä ja että evakuoitavien pyrkimys yhteistyöhön voi hidastaa poistumista.Väitöskirjassa kehitetyt henkilöliikenteen estimointimallit ja -algoritmit mahdollistavat hissien tehokkaamman ohjaamisen ja osa menetelmistä on jo tuotannossa KONE...

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Section: Theoretical Foundationmentioning

confidence: 99%

The Elevator Trip Origin-Destination Matrix Estimation Problem

Kuusinen¹,

Sorsa²,

Siikonen³

2015

Transportation Science

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“…The general format for an OD matrix is shown in equation (4). All the diagonal elements are equal to zero, as it is assumed that passengers are rational and would not travel from a floor to the same floor.…”

Section: Od Matrixmentioning

confidence: 99%

“…A building has two entrance floors (B and G) and four occupant floors (1)(2)(3)(4). The percentage ARs from the two entrances are 0.2 and 0.8 from B and G, respectively.…”

Section: Random Generation Of Passengers Using the Od Matrixmentioning

confidence: 99%

“…Examples of traffic mix conditions that are believed to be representative of the lunchtime peak traffic conditions in many modern office buildings include: 40%:40%: 20%; 1 45%:45%:10%; 2 42%, 42%, 16%; 3 incoming, outgoing, and interfloor traffic, respectively. In addition, it is possible to calculate the round trip time for general traffic conditions under the Poisson arrival process assumption 4,5 or the plentiful passenger supply assumption. 6 Based on these last two points, this paper thus presents an integrated framework for carrying out an elevator traffic design under general traffic conditions (i.e., any traffic mix of incoming traffic, outgoing traffic, and interfloor traffic).…”

Section: Introductionmentioning

confidence: 99%

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An integrated framework for elevator traffic design under general traffic conditions using origin destination matrices, virtual interval, and the Monte Carlo simulation method

Al-Sharif

Alqumsan

2015

Building Services Engineering Research and Technology

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The conventional design methodology for elevator traffic analysis has been applied to the case of up-peak traffic (or incoming traffic conditions). The only user requirements are usually the expected arrival rate (AR%) expressed as a percentage of the building population requesting service in the peak 5 min and the target interval. The interval as classically used will be referred to as the physical interval in this paper as it is only relevant for the case of a single entrance and incoming traffic conditions. This paper presents an integrated methodology for the design of elevator traffic systems for the general case of mixed traffic conditions. It presents a fully integrated framework that covers the steps from user requirements to the selection of the number of required elevators. The user requirements describing the traffic conditions can be specified by the user, expressed as the AR%, the mix of incoming traffic, outgoing traffic, and interfloor traffic. This paper derives equations that can be used to combine the mix of traffic, the floor arrival percentages, and the floor population percentages into an origin-destination matrix. The origin-destination matrix is then adjusted and normalized in order to account for rational passenger behavior (i.e., a passenger will not travel to the same floor that he or she is at). A method is presented for the random generation of passenger origin-destination pairs using the origin-destination matrix (which is necessary when using the Monte Carlo Simulation (MCS) method to calculate the round trip time). A novel equation for evaluating the round trip time under the assumption of equal floor heights and top speed attained in one floor journey is derived and used. The equation is derived using a stepwise derivation and verification process. The verification is carried out against the MCS method for finding the value of the round trip time. The concept of a virtual interval (as opposed to the conventionally used physical interval usually used in elevator traffic system design) is introduced in order to allow the selection of the number of elevators Downloaded from to be carried out. The virtual interval is the average value of the time between the consecutive reversals of the elevators in the group. Practical application The methodology presented in this paper allows the elevator traffic system designer to convert the user requirements specification (in the form of an arrival rate and the percentage floor strengths) into an origin-destination matrix. The origin-destination matrix is a more suitable tool for calculating the expected value of the round trip time and consequently carrying out an elevator traffic design. Thus, this methodology represents a vital step in the design process.

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“…Examples of traffic mix conditions that are believed to be representative of the lunch-time peak traffic conditions in many modern office buildings include: 40%:40%:20% [10]; 45%:45%:10% [11]; 42%, 42%, 16% [12]; incoming, outgoing and inter-floor traffic, respectively. In addition, it is possible to calculate the round-trip time for general traffic conditions under the Poisson arrival process assumption ( [13,14]) or the plentifulpassenger-supply assumption ( [15,16]).…”

Section: Introductionmentioning

confidence: 99%

A Universal Methodology for Generating Elevator Passenger Origin-Destination Pairs for Calculation and Simulation

Al-Sharif¹

2021

Smart Cities - Their Framework and Applications

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The origin-destination matrix is a two-dimensional matrix that describes the probability of a passenger travelling from one floor in the building to another. It is a two-dimensional square matrix. The row index denotes the origin floor and the row index denotes the destination floor for the passenger journey. A previous chapter described the methodology for constructing the origin-destination matrix (OD matrix) from the user requirements. However, that chapter placed the restriction that any floor must either be assigned as an entrance floor or an occupant floor, but not both. This chapter relaxes this restriction and shows a method for developing the origin-destination matrix that allows any floor to either be an entrance floor; an occupant floor; or both. The origin destination matrix can be compiled using three sets of parameters: the mix of traffic (incoming traffic, outgoing traffic, inter-floor traffic; and inter-entrance traffic); the floor populations; and the entrance percentage bias (i.e., the relative strength of the arrivals at the entrance floors). The origindestination matrix can be used for the generation of random passenger origindestination pairs (which is necessary when using the Monte Carlo Simulation (MCS) method to calculate the round-trip time or in elevator traffic software).

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Lift traffic analysis: Formulae for the general case

Cited by 16 publications

References 1 publication

The Elevator Trip Origin-Destination Matrix Estimation Problem

The Elevator Trip Origin-Destination Matrix Estimation Problem

An integrated framework for elevator traffic design under general traffic conditions using origin destination matrices, virtual interval, and the Monte Carlo simulation method

A Universal Methodology for Generating Elevator Passenger Origin-Destination Pairs for Calculation and Simulation

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