Traffic_demand in Office Building

September 2011 | ELEVATOR WORLD | 113

Focus onTraffic Analysis

Lift Passenger Demand in Office Buildingsby Dr. Richard Peters, Rory Smith and Elizabeth Evans

AbstractThe number of passengers want-

ing to use lifts to travel to and fromthe lobby and between floors in abuilding has a significant effect onthe quality of lift service experiencedby each passenger. The traditionalassumptions of lift passenger de-mand in office buildings are com-pared to measurements taken inmodern buildings. The differencesbetween traditional and modern pat-terns of passenger demand in officebuildings are also discussed. The sig-nificance of these differences on lift-system design is explored.Introduction

The quantity of passengers to betransported by a lift system is a pri-mary consideration in lift-system de-sign. Our research indicates thatpassenger demand in modern officebuildings is significantly differentthan the assumptions formed manydecades ago but still applies to mostmodern designs. The number andtype of lifts required to provideproper and efficient lift service mayneed to be revised based on thesefindings. These changes in lift-sys-tem design have favorable economicand environmental consequences.Historical Representations of Passenger Demand

A plot of passenger demand de-picts the level of passenger traffic ina group of lifts over a period of time.Figure 1 shows estimated passengerdemand for a working day of an of-fice building with a population of1,000 people. This has been gener-ated by applying the example of of-fice passenger demand presented byGeorge Strakosch in The VerticalTransportation Handbook.[1] In this

representation of passenger de-mand, passengers traveling up thebuilding are shown in the top sectionof the graph, with passengers travel-ing down in the lower section.

Figure 1: Passenger demand based on GeorgeStrakoschs presentation

Figure 2 plots passenger demandbased on a similar pattern of officedemand developed by Dr. Gina Barneyand presented in CIBSE Guide D[2]

Lift Traffic Analysis Design and Con-trol[3] and The Elevator Traffic Hand-book.[4] The patterns of passengerdemand presented by Strakosch andBarney are very similar. They havea pronounced up-peak in the morn-ing, a pronounced down-peak in theevening, two small lunchtime up-peaks and two small lunchtimedown-peaks. Additionally, periodsof balanced two-way traffic can be seen.

Figure 2: Passenger demand based on Dr. Gina Barneyspresentation

The basis of these presentations isbelieved to be data acquired at a sin-gle building in the U.S. in the early1960s. Many, including the authors

Dr. Richard Peters is a director of Peters Re-

search, Ltd. He has a degree in Electrical Engineer-

ing and a doctorate for research in Vertical Trans-

portation. Peters has been developing traffic analysis,

simulation and dispatching software since 1986.

Elizabeth Evans joined Peters Research in 2005

to assist with commercial aspects of the business.

She has since been involved with elevator traffic

analysis, including research projects and traffic studies.

Rory Smith is director of Operations for

ThyssenKrupp Middle East. He has a B.S. in Business

Administration and an MS in Engineering and is a

PhD candidate at the University of Northampton,

U.K. He has 42 years of experience in the lift industry.

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114 |WWW.ELEVATORWORLD.COM | September 2011

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Traffic Analysisof this paper, believe this building and its pattern of trafficdemand to be typical of major city office buildings duringthis period. It was generally believed that the most demand-ing traffic type was the morning up-peak. This belief wasreinforced by research conducted by Barney that showedthat lifts have between 20-60% more capacity during nonup-peak conditions.[4]

It has been assumed by many in the lift industry thatmost office buildings had a pattern of passenger demandsimilar to those in Figures 1 and 2. Many papers havebeen written about how lift dispatchers should handle thedifferent types of traffic apparent during the working day:up-peak, down-peak, lunch and balanced two way.[5] Addi-tional papers have been written about methods to eitherpredict or detect the type of traffic that existed so that theappropriate dispatching algorithm could be applied.[6]

Anyone who has visited major cities over the last 40years can likely attest to the fact that many things havechanged. One may reasonably question how applicable apassenger demand pattern that existed more than 40years ago is to a present-day building.Modern Buildings

How people use lifts and the traffic patterns that theiruse generates has changed since 1923, when BassetJones published formulae for the expected number ofstops a car will make during a round trip.[4] Summarizingthe results of a series of peak-time traffic surveys carriedout between 1993 and 1997, Peters Research Ltd. con-cluded that morning traffic peaks are less marked inbuildings than they were when traditional up-peak designcriteria were formulated. In work-related buildings occupiedduring the day, the busiest period appears to be over thelunch period.[7] In 2002, Bruce Powell, discussing modernoffice buildings, states, Two-way traffic at noontime isoften a more severe test of elevators than up-peak.[8]

In 2000, M. Siikonen presented a traffic pattern thatrepresents traffic measured in a modern installation.[9]

Siikonen presented data as a stacked area graph, but forconsistency with Figures 1 and 2, the same data is pre-sented in Figure 3 showing incoming and outgoing trafficseparately. This pattern is quite different from that pre-sented by Barney and Strakosch. Siikonen shows a lunchup-peak that is the same size as the morning up-peak.Additionally, the down-peak at lunch is more intensethan the evening down-peak. Both the Barney andStrakosch lunch periods show a down-peak followed byan up-peak, which is followed by smaller down- and up-peaks. These double peaks do not occur in the Siikonenpattern. These observations raise the question, Are thedifferences in the patterns due to the unique nature of thebuilding studied by Siikonen, or have traffic patternschanged over the years?

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Figure 3: Passenger demand based on Siikonens presentation

The traffic pattern presented by Siikonen could bebuilding specific, or it could represent a basic change intraffic patterns. In order to better understand modern lifttraffic, data was collected at a number of office buildingsin different parts of the world including Europe, NorthAmerica and the U.A.E. In most cases, data was collectedby manual count. However, in one building, data fromthree groups of lifts in a corporate headquarters buildingwas gathered electronically.Manual CountsFigure 4 shows the results of lift traffic surveys for

seven separate groups of lifts.[10] The surveys were un-dertaken applying a methodology defined by Peters Re-search.[11] The passenger demand is normalized againstobserved population to allow results to be compared be-tween buildings. The observed population is the maxi-mum occupancy of the building on the day of the surveyand is often significantly lower than that reported bybuilding management.

Figure 4: Passenger demand based on manual traffic surveys

Automatic CountsIt is difficult to automatically count the number of pas-

sengers using lifts with conventional control systemswith up and down call buttons on the landings,[2] as they

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Traffic Analysisonly count calls, and there is often more than one personbehind a call. With a destination-control system (DCS),each passenger registers which floor he or she wants totravel to on the landing. A DCS based on the estimatedtime of delivery algorithm[12] was used to log the opera-tion of the lifts, including every destination call. Thelogged data was replayed in Peters Researchs ELEVATEsimulation program mapping destination calls to people,resulting in an estimate of passenger demand.[13]

Figures 5-7 record the estimated passenger demandfor the three groups of passenger lifts in a corporateheadquarters building in the U.S.

Plotting data for a whole week demonstrates a highlevel of consistency in passenger demand. Each group hasa recognizable passenger-demand pattern or signature.Up-Peak Traffic

In modern buildings, there is often a significantamount of outgoing traffic during the morning incomingup-peak. A major contributor to this is people traveling tothe main lobby or to a staff restaurant. A common practice

Figure 5: Low rise passenger demand

Figure 6: Mid rise passenger demand

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ContinuedFocus on

Traffic Analysisis for a person to arrive for the first time at his or her deskafter taking the lift up, as they want to be seen as havingarrived by their superiors and coworkers. They then takethe lift back down, make their purchases and return totheir workstation by taking the lift up. This process in-volves two incoming trips and one outgoing trip.

The trend to ban smoking in public and work placeshas also been noted by building managers to increase theoutgoing demand during the morning incoming up-peakperiod. On average, the mix of traffic in modern buildingsduring the morning up-peak was found to be approxi-mately 85% incoming, 10% outgoing and 5% interfloor.Lunch Traffic

Siikonen explains part of the differences from Barneyand Strakoschs classical representations by stating,Flexible working hours creates a heavy down-peak before lunch hour.[9] The lunch hour is actually nearertwo hours. It is not unusual for the incoming traffic andoutgoing traffic at lunchtime to be of the same order ofmagnitude as the incoming traffic in the morning up- peak,

Figure 7: High rise passenger demand

Figure 8: Low rise passenger demand signature

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Traffic Analysisand the outgoing traffic during the evening down- peak.Eating habits have changed over the years. It is now lesscommon to bring a packed lunch to eat at your desk. Allthe major office buildings we surveyed were in closewalking distance of a range of eat-in and take-out restau-rants. Many also had dedicated staff restaurants.In 1970, U.S. citizens spent US$6 billion on fast

food.[14] By 2006, that figure had increased to US$163.5billion.[15] Even adjusting for inflation, it is obvious thatAmericans were eating out more often. The story in theU.K. is similar. The BBC announced that U.K. householdswere spending more money on eating out than on buy-ing food to eat at home.[16] On average, the mix of traf-fic in modern buildings during the busiest part of lunchwas found to be 45% incoming, 45% outgoing and 10%interfloor.Afternoon and Down-Peak TrafficNone of the groups surveyed have the sharp down-

peak seen in the Barney and Strakosch pattern. A sharpdown-peak would be expected in buildings with peoplewho have strict working times. This is unusual in modernoffice buildings with professional workers. A significantportion of office workers are working later than in previ-ous years. There is often sustained activity in the lateafternoon. The afternoon up traffic may be related topeople returning to the office after visiting clients. Sometraffic may also be attributed to couriers such as FedEx,DHL and UPS. DHL began shipping documents from SanFrancisco to Honolulu in 1969,[17] while FedEx startedoperations in 1973.[18] The traffic generated by thesecouriers did not exist when the Strakosch and Barneypatterns were developed.A Changing WorkforceThe use of computers has changed the makeup of the

workforce. Previously, office workers included many people

Figure 9: Mid rise passenger demand signature

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Traffic Analysis

Conclusions The pattern of passenger demand measured in oursurveys closely resembles the traffic results presentedby Siikonen.

Traffic in modern office buildings is markedly differentfrom that of the past.

While peak traffic periods still exist today, the ampli-tude of those peaks is not as great, and the duration islonger. Total passenger demand is normally (but notalways) greater at lunchtime than during the morningup-peak. Major down-peaks are rarely seen.

Lift-control systems should be designed to detect andmanage the new patterns of passenger demand inmodern buildings.

Selection of new lift systems should be based on moderndata as opposed to historical measurements of passen-ger demand. In many instances, this will result in smallerand more energy-efficient lifts being specified.

References[1] Strakosch, G. The Vertical Transportation Handbook. 3rd ed., Elevators

and Escalators. New York: Wiley; 1998.[2] CIBSE, The Chartered Institution of Building Services Engineers. CIBSE

Guide D: Transportation Systems in Buildings, Norwich: CIBSE; 2005.[3] Barney, G. & Dos Santos, S. Lift Traffic Analysis Design and Control.

London: Pereginus; 1977.[4] Barney, G. Elevator Traffic Handbook. London: Spon Press; 2003.[5] Bahajt Z & Bittar J, Inventor; Otis. Automated selection of high traffic

intensity algorithms for up-peak period. U.S. patent number5,168,133. December 1, 1993.

[6] Qun, Z.; Ming S.; and Ling, T. Elevator Traffic-Flow Prediction Basedon Gaussian Mixture Model. ELEVATOR WORLD, 2006.

[7] Peters, R.D. Vertical Transportation Planning in Buildings. British Libraryreference DX199632 (1998)

[8] Powell, B. Elevator Planning and Analysis on the Web. ElevatorWORLD, 2002.

[9] Siikonen, M. Elevator Technology 10, IAEE, Israel, 2000[10] Peters Research Ltd., private client reports.[11] Peters, R. & Evans, E. Measuring and Simulating Elevator Passen-

gers in Existing Buildings. Elevator Technology 17: Proceedings ofELEVCON 2008 (The International Association of Elevator Engineers).

[12] Smith, R. and Peters, R. ETD Algorithm with Destination Dispatchand Booster Options. ELEVATOR WORLD, 2002.

[13] Peters, R. & Smith, R. Analysis of Elevator Performance and Passen-ger Demand with Destination Control. Elevator Technology 17, IAEE,Israel, 2008.

[14] Wikipedia. Fast Food. [Cited July 21, 2007]. [15] How Stuff Works. The History of Fast Food. [Cited July 21, 2007]. [16] BBC. Eating Out Overtakes Home Dinning. [Cited July 21, 2007] [17] DHL company Portrait [Cited December 6, 2008] [18] FedEx History. [Cited December 6, 2008]

Figure 11: Passenger demand range for major office buildings

dedicated to clerical tasks. For example, typing poolswere common, but in a modern building, there are virtu-ally no typewriters. People generate their own correspon-dence using e-mail and word processing programs. Cler-ical workers have been replaced by knowledge workersand by workers who have more customer interface. Cler-ical workers were more likely to have fixed workinghours, which contributed to higher morning and eveningtraffic peaks.In recent years, increased globalization has led to a

change in working patterns. Business is now conductedacross international time zones, and working hours havebecome more flexible to encompass this. The traditional9:00 a.m. to 5:00 p.m. working day has given way to a 24-hour working environment, and as a result, demand forlift services has also changed.New Design CriteriaThe highest demand is seen in buildings with small

populations. This is because fewer people represent ahigher percentage of the building population. Thesepeaks are not sustained, and are thus manageable with-out specific design. Figure 11 shows the range of totalpassenger demand measured in a major office with anobserved population in excess of 1,000 people. Total de-mand includes incoming, outgoing and interfloor traffic.In most modern office buildings, there is a greater de-

mand at lunchtime than in the morning. However, bothmorning and lunch periods need to be considered as partof the design process. In the morning, the lifts are mostcrowded, as people are mostly traveling in one directionand are in the car together. At lunchtime, incoming andoutgoing traffic are not in the car together, which makesthe cars less crowded (provided that the building is notunder-lifted). However, at lunchtime, the cars stop moreoften, leading to longer waiting times.

Figure 10: High rise passenger demand signature

Traffic_demand in Office Building

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