Influence of color on fire vehicle accidents

8/13/2019 Influence of color on fire vehicle accidents

1/8

Journal of Safety Research, Vol. 26, No. I. pp. 41-48, 1995Copyright Q 1995 National Safety Council and Elsevier Science LtdPrinted in the USA. All rights reserved0022-4375/95 9.50 + .OOPergamon

0022-4375 95)00001-l

Influence of Color on Fire Vehicle AccidentsStephen S. Solomon and James G. King

Fire fighting equipment is predominantly red or red/white. However, thisstudy reports that if other factors are the same, the probability of a visibility-related accident for a red or red/white pumper is greater than the probabilityfor a lime-yellow/white pumper. Data from public safety departmentsrecords regarding fire pumper runs and accidents that occurred over a fouryear period in a single city are reviewed and tabulated. It is shown that lime-yellow/white fire pumpers are significantly statistically safer than red andred/white fire pumpers.

PROBLEM

The National Safety Council reports that in1988 motor-vehicle accidents were the sixthleading cause of death and the leading causeof accidental death (National Safety Council,1991). During the period of this study(1984-1988) and continuing through 1990,the overall number of firefighter injuries hasStephen S. Solomon, BS, OD, attended The PennsylvaniaState University and graduated from the PennsylvaniaCollege of Optometry. He is a Fellow of the AmericanAcademy of Optometry (F.A.A.O.), and has publishednumerous safety and visibility articles including those in themajor American fire journals. Dr. Solomon has receivedprofessional recognition for his contributions in visibilityand safety research. A practicing optometrist and aconsultant to industry in the areas of color and safety, he isalso a 36 year volunteer firefighter and holds the rank offire commissioner.James G. King has BS and AB degrees in Electrical En-gineering and Linguistics from The University of Rochester.He is employed at Loral Federal Systems Company as aSenior Engineer/Manager and currently manages systemsengineering (including human engineering and systemssafety engineering) for a military helicopter program. He haspublished several technical disclosures and holds patents

dealing with electronic circuits implementing numericalgorithms. He is a 25 year veteran of the volunteer fire ser-vice and emergency medical service.Spring 1995Nolume 2QNumber 1

remained relatively constant. The NationalFire Protection Association (NFPA) estimatedthat for the year 1990, the first year these datawere compiled, there were 11,325 motor-vehi-cle accidents involving fire department emer-gency vehicles. Moreover, 1,300 firefighterswere injured while responding to or returningfrom alarms (Karter & Le Blanc, 1991). TheNFPA did not report on civilians killed orinjured in those accidents.Fire vehicle accidents are life-threateningand expensive, not only to those in the emer-gency vehicle, but also to those in other vehi-cles involved in these accidents. Beyond theimmediate consequences of the accidents arethe effects due to delayed or absent response,such as property and life loss at fire scenes.Injured firefighters may become eligible forcompensation and disability payments. Thecommunity must repair or replace the damagedapparatus and adjust for temporary decreases inmanpower and equipment. To provide someperspective, the cost of a typical fire departmentpumper is over 200,000, and an aerial laddermay cost more than two times that amount.The most costly accidents, in terms of[fire] vehicle damage and personal injury,

41


2/8


3/8

1.

2.

3.

Fire pumpers painted lime-yellow/whitehave an accident probability equal to thatof fire pumpers painted red or red/white.In daylight with lights and siren operating,fire pumpers painted lime-yellow/whitehave an accident probability equal to thatof fire pumpers painted red or red/white.In intersections, tire pumpers painted lime-yellow/white have an accident probabilityequal to that of fire pumpers painted red orred/white.

METHOD

A retrospective study of fire pumper vehi-cle accidents in a single city provides statisticswith respect to vehicle color. While the proba-bility distribution of these accidents isPoisson, the statistical analysis, whichemploys Bayes Theorem, is independent ofdistribution type. Since the number of acci-dents is small, accurate estimation of proba-bility by vehicle color is suspect. Instead, theprobability of a red or red/white fire pumperaccident and the probability of a lime-yel-low/white fire pumper accident are comparedas a ratio. Supplementing the probability anal-ysis, in addition to the accident types of thehypotheses, injury and towaway accidents arecalculated on a run basis. Also, national vehi-cle crash data are contrasted with crash datafor the city of Dallas in general and DallasFire Department pumpers specifically.

National vehicle crash data are from theNational Highway Traffic Safety Administra-tion. The Dallas motor-vehicle accident dataare from the Dallas Department ofTransportation and the Texas Department ofPublic Safety. The Dallas Fire Departmentcrash data are from information supplied bythat organization and the Texas Departmentof Public Safety. The data gathered cover afour year period: October 1, 1984, throughSeptember 30, 1988.Control of Variables

By studying a single urban fire departmentwith vehicles of both color categories in ser-vice at the same time, the confounding of sev-eral variables was reduced and balanced.These include: weather conditions, lawenforcement regulations, traffic densities,apparatus operation, driver training, vehicleinspection and maintenance, and length ofrun. All fire pumpers in the study wereequipped with emergency lights and sirens.As a control of vehicle size, the fire vehiclesused in the study exclude aerial trucks, ambu-lances, and chiefs vehicles.

Data Sources Analysis Procedure

In the 197Os, the City of Dallas, Texas,began purchasing fire vehicles with lime-yellow body paint and white upper cabpaint. This continued until the early 1980s.At that time, a switch was made to redbody paint with white upper cab paint.Prior to the purchasing of lime-yellow/white vehicles, the fleet primarily consistedof all red vehicles.From information supplied by the DallasFire Department, it is possible to determinefor each year the number of lime-yellow/whitefire pumpers, the number of red and/orred/white fire pumpers, and the total numberof runs each color group performed.

In this study, multiple-vehicle and single-vehicle accidents are counted if the dynamicsinvolve visibility between at least one civilianvehicle and a pumper. Accidents, in which thepumper is the only moving vehicle, are notcounted if it is judged that the visibility of thepumper is not a factor. All accident reports arecarefully reviewed to ascertain color. If firevehicle color is not stated in the police offi-cers report, information such as identificationnumber(s) and vehicle age is correlated withother Dallas Fire Department records in orderto determine color.

An accident is said to be at an intersectionif the diagram or narrative of the police offi-cers report indicates that the accidentSpri ng 1995Nolume 26/Number I 43

The accident data detailing the Dallas FireDepartment accidents are obtained from themotor-vehicle accident report forms filed withthe Texas Department of Public Safety. Thesereports reflect all police-reported accidentsinvolving the Dallas Fire Department for thedates included in the study.


4/8

occurred in the intersection or as a result ofpassing through an intersection. Injuries andvehicle removal method are reported in spe-cific sections of the police officers report.Accident date and time from the police offi-cers report, and sunrise and sunset data froman almanac, are used to determine ambientskylight (day, night, or twilight). Moon-phaseand cloud-cover are not considered.The use of lights and siren is determinedfrom analysis of the police officers report:narrative section, factors and conditions sec-tion, and arrests and charges section. Theobjective of the statistical analysis is toestablish whether or not the color of firepumpers affects accident probability; not todetermine the absolute accident probabilities.To do so, the unknown probabilities are com-pared by hypothesizing equality (a = 1,below), and then this hypothesized equalityis discredited.Two experiments are defined: One, Er, con-sists of red and red/white pumper runs. Theother, Ey, consists of lime-yellow/whitepumper runs. (A run is defined as a responseto an emergency call during which a firepumper is driven to an incident scene withaudible and luminant warning devices activat-ed, and subsequently returns without warningdevices activated. Statistically, each run isconsidered to be a repetition of a trial,resulting in an accident event or not-an-acci-dent event.) Er has the quantity of Nr trials.Ey has the quantity of Ny trials. The probabili-ty of a red or red/white pumper accident in asingle trial is designated Pr. The probabilityof a lime-yellow/white pumper accident in asingle trial is designated Py.A third combined experiment, Eb, has Nbtrials (runs), Nb = Nr + Ny.Let a lime-yellow/white pumper run bedesignated Yrun, and a red or red/whitepumper run be designated Rrun. Assumingruns are random:P((Yrun))=Ny/NbP((Rrun))=Nr/Nb

Let the occurrence of an accident be desig-nated Aacc, a lime-yellow/white accident bedesignated Yucc, and a red or red/white accidentbe designated Race. The conditional probabilityof a lime-yellow/white pumper accident given

any one accident is written P( ( Yucc)I Aacc)).Given the independence of runs:P((Yucc)) = P({Yrun)I(Aacc))P((Rucc)) = P({Rrwz)l(Aacc))P({ Yucc)I(Aucc))P(( Yucc) n (Aucc))= by definition

P((AaccJ)P({Yaccl)= by set theoryP(( Yucc) U (Rucc))

Py*P((Yrun))= by Bayes Theorem.Py P(( Yrun)) +Pr* P({Rrun})

For a real number a > 0, Pr = a Py.Therefore:

P( (Yucc)l(Aucc))P(I Yrun))

P(( Yrun)) + a. P((Rrun))NylNb=

(NylNb)+u*(NrlNb)NylNr= .

(Ny/Nr)+uLetting p = P( ( Yucc)I(Aucc)) and r = Ny /Nr, yields:

p = r/(r + a).Now, if there are j accidents in total, theprobability lime-yellow/white pumper acci-dents will occur exactly k times in j accidentsis the binomial distribution:

jP( (k times)) = pk ( l-p)j-kk (j-k)j

= k (j-k) [r/ r + u)lk I - r/(r + u)]jmk.44 Journal of Safet y Research


5/8

The probability that the total number of lime-yellow/white pumper accidents does not exceedthe observed number of lime-yellow/whitepumper accidents, i, in the observed total num-ber of accidents,j, is given byP({O I k I i}) ;iOP [k times}) .

RESULTS

The calculated conditional probability thatlime-yellow/white pumper accidents are asobserved or fewer, given that a lime-yellow/white pumper accident is equally asprobable as a red or red/white pumper accident,is presented in Table 1. Assuming the nullhypotheses are correct, one would expectresults this extreme in less than 5% of a largenumber of similar analyses. Therefore, it isprobable that one color is safer than the other.As illustrated in Tables 1 and 2, the indicationis that lime-yellow/white is safer than red orred/white in all categories. Moreover, Figure 1shows that the probability of the observednumbers of lime-yellow/white accidents ismaximum when the probability of a red orred/white accidents is more than three times theprobability of a lime-yellow/white accident.Red or red/white fire pumpers performed153,348 runs, and lime-yellow/white firepumpers performed 135,035 runs. Accordingto the Texas Department of Public Safety, therewere 28 accidents. Of these, 8 were discardedas not visibility related (in 6, a pumper struck a

parked or unmoving car; in 2, a pumper strucka stationary object). Table 3 summarizes thecharacteristics of the included 20 accidents.Note that for the 20 included accidents,16 accidents involved red or red/white firepumpers and produced 10 towaway and 7injury accidents. The 4 lime-yellow/whitefire pumper accidents produced 2 towawaysand 1 injury accident. The data in Table 3also show that daylight accidents accountfor 85% of all accidents and 86% of inter-section accidents.For the 11 intersection accidents involvingred or red/white fire pumpers, 7 were tow-away accidents and 5 were injury. The 3intersection accidents involving lime-yel-low/white fire pumpers had 2 towaways andnone with injuries.For the years encompassed by this study,Table 4 summarizes the estimated total motor-vehicle accidents as a function of miles drivenfor the United States and for the City ofDallas. Also presented are the City of Dallasestimated accidents per million miles for redor red/white fire pumpers and lime-yellow/white fire pumpers.From these estimates, it can be reasonedthat fire pumpers appear to be involved in sig-nificantly more accidents than motor vehiclesas a whole. It is of interest that in Dallas theestimated accidents per million miles for redor red/white fire pumpers are more than 22times (contrasting with lime-yellow/white firepumpers at more than 10 times) that of thetotal of Dallas motor vehicles. The operationof fire pumpers, especially on emergencycalls, can be interpreted to be very dangerous.

TABLEPROBABILI TIE S OF OBTAINED RESULTS UNDER THE NULL HYPOTHESES FOR FI RE PUMPER ACCIDENTS

Equal LIY and RFiwProbabilitv Hvoothesls

Accident Counts Probability ofobserved or fewer LIY

(AccidentTybk) I LiY Total accidentsIll Types ................................20 0.013Day with lights and siren ..................... 3 14 0.048Intersection ..... ......................... 3 14 0 048Key. RRw Red or Red/Wh,te

LiY Lime-Yellow/White

1.These low probability values ca?.t doubt on the validity of the hypotheses, thus lmplyng thaf color IS a factor I fire pumperaccadents.2 Presummg the rano of Ikme-yellow/wh te runs to red or rediwhlte runs IS the same as It IS for All Types

Spring 1995Nolume 26LVumber I 4s


6/8

TABLE 2FIRE PUMPER VISIBILITY-RELATED ACCIDENTS BY COLOR PER HUNDRED-THOUSAND RUNS

(CITY OF DALLAS, TX; lo/84 - 9/88)

Accident TypeA,, types ............................................Day with lights and siren ..................................Intersection ...........................................Tawaway ............................................,n,ury ...............................................

LIY FiRw(per 100,000 runs)

3.0 10.42.2 7.22.2 7.21.5 6.50.7 4.6

Key: RRw Red or RediWhlteLIY Lime-Yellow/White

CONCLUSIONS

With focus on the color of the fire pumpersand the number of fire pumper accidents, analy-ses were conducted on run and vehicle informa-tion supplied by the Dallas Fire Department andfire vehicle accident data from the Dallas policereports on file with the Texas Depart-ment ofPublic Safety. The effect of color on the risk ofmultiple-vehicle accidents or single-vehicle visi-bility related accidents involving fire pumpers hasbeen assessed. The conclusion is that the likeli-hood of having a visibility-related multiple-vehi-cle accident or a visibility-related single-vehicleaccident for a red or red/white fire pumper isgreater than for a lime-yellow/white fire pumper.Perhaps it is more than three times as great.

Further, in those accidents involving a lime-yel-low/white fire pumper, there is evidence that thelikelihood of towaway or injury damage is less.Limitations

To minimize the effects of confounding vari-ables, a single city was used. However, this con-stricts the number of accidents. Future, broader-based studies are warranted. In addition,research is required on the effects of vehiclecolor on the remainder of the fire fleet and onhighway vehicles in general.

Consequences and ImplicationsAll fire pumpers in the study were equip-ped with emergency lights and sirens. In 80%

FIGURE 11 r0.9wigure 1: Probability of the observed number of LiY accidents0.8 given the number of same type accidents underthe null hypothesewersus the ratio of RRw to LiY0.7 accident probabilities.. 0.6.-=:aj?j 0.52n. 0.4 Daytime accidents andintersection accidents3 LiY, 11 RRw

Ratio = Pr/Py = a46 Journal of Safety Research


7/8


8/8

benefits, and the cost of supplemental person-nel; health, life, and workers compensationinsurance costs; the costs of vehicle repair andpremature replacement; and the expense of lit-igation resulting from fire vehicle accidents.Municipal liabilities might include the costs ofextended disability or lost time expenses.Insurance rates are based on risk and competi-tion. It can be expected that proven reducedrisk could be part of a negotiation for reducedrates. Actuarial expectations for firefighterscould also be expected to be adjusted basedupon change in death rate experience.The benefits of shifting the fire vehiclecolor paradigm from red to lime-yellow makeit imperative that officers and officials respon-sible for purchasing these vehicles be encour-aged to accept the change. The representativesof firefighters should be seeking safer vehiclesfor their constituents. Firefighters themselvesshould be educated as to the personal benefitgained in improved probability of safe trans-port to and from the alarm scene.Realizing no single factor will halt allvehicle accident injuries and deaths, a com-posite of programs can have a strong impact.While we conclude that lime-yellow/whitefire pumpers are safer to operate, from an epi-demiology perspective, use of lime-yellowcolor may have significant beneficial high-way implications beyond the fire service.

ACKNOWLEDGEMENTS

We are indebted to Lionel Weiss, PhD(College of Engineering, School of Operations

Research and Industrial Engineering, CornellUniversity) for the statistical analysismethod; to Donald C. Gause, Professor(Binghamton University) for statisticaladvice; and to John Shafer, PhD (IBMFederal Systems, Retired), Human FactorsConsultant, for editorial comment.

REFERENCESAllen, M. J. (1970). Vision and highw ay safety (pp. 88,174-175). Philadelphia: Chilton Book Company.DeLorenzo, R. A. (1992). Bright light, big noise: Howeffective are vehicle warning systems? Journal of

Emergency M edical Serv ices, 17.60.Federal Aviation Administration. (1986, July 1 ).Advisorycircul ar No. AC 150/5210-5B. Washington, DC: Author.Karter, M. J., Jr.. & Le Blanc, P. R. (1991, November/December). U.S. fire fighter injuries - 1990. NationalFire Prot ecti on Associat ion Journal , 46.Lahr, L. E., & Heinsen, A. C. (1959). Visibility of colors: Afield study of the relative visibility of various colors.Cali forn ia Fish and Game Quart erl y, 4~5~208-209.Leonard, F. M., & Sleight, R. B. (1967, January).Conspicuous colors for pol ice vehicles. Paper deliveredat the Highway Research Board, 46th Annual Meeting.Washington, DC: Century Research Corporation.Los Angeles Fire Department. (1983, October 5). Accidentprevention (Operations circular No. 83-6, p. 1).Nathan, R. A. (1969, September). Whats the safest color fora motor vehicle? Trc ic Safet y, 69, 13.National Safety Council. (1991). Accident facts 1991edition, (p. 6). Chicago: Author.New York State Department of Motor Vehicles. (1990,February 2). Summar y of mot or vehicle accidentinv olv ing ir e vehicles [in] 1988 (MV-144A, pi 2). Stateof New York Department of Motor Vehicles.Solomon, S. S. (1984, June). The safety color. Fi rehouse, 9,106-107.Southall, J. P. (1961). Int roducti on to physiol ogical opti csP. 273). New York Dover Publications.Traquair, H. M. (1949). An introduct i on to cl inicalperimetry (pp. 10-11). Saint Louis: D. V. Mosby.

48 Journal of Safety Research

Documents

Influence of color on fire vehicle accidents