Parking Related Crash Characteristics (Article)

7/29/2019 Parking Related Crash Characteristics (Article)

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Parking-Related Crash Characteristics

Characteristics of crashes at

parking lots were investigated

and the significant risk

factors related to the traffic

environment, driver, and vehicle

were identified using logistic

regression models. The study

found that crashes at parking

lots are more likely to occur

while the drivers vision is

obstructed by building/fixed

objects, with a parked car, and

while backing the vehicle.

BY CHOWDHURY SIDDIQUI, M.S., PH.D., MOHAMED ABDEL-ATY,

P.E., PH.D., AND TAHERA ANJUMAN, M.S., E.I.T.

PARKING LOTS ARE OFTEN Aconfusing environment with unclear speedlimits or traffic rules.1 Although park-ing lots are an important feature of thetransportation infrastructure, not muchis known about their safety issues. Due tolow speeds, crashes at parking lots are oftenless severe than others, but result in highnumbers of property damage only (PDO)crashes. As cited by Retting et al.,2 parkinglot crashes constitute about one-fifth of all

low-speed urban crashes. This type of crashis different from a typical roadway crash.These crashes have been rarely addressed inthe road safety literature, possibly becauseof their less severe nature.

According to the Florida Departmentof Highway Safety and Motor Vehicles,15,818 crashes in Florida in 2007 (about6.9 percent of total crashes) occurred atparking lots. The factors we analyzedinclude characteristics of a crash event,driver information, and vehicle character-istics. Distributions of some of the factorsassociated with parking lot crashes arepresented in Figure 1.

The logistic regression model iswidely used in road safety studies wherethe dependent variable is binary.3,4 Mul-tivariate logistic models were consideredsuitable for this analysis because they es-timate the probability of an event occur-ring or not (i.e., dichotomous response)by testing the association between thebinary response variable and significantpredictors. To assess the effect of a unit

increment of any predictor, odds ratios(ORs) were calculated. Because most

of the factors werecategorical variableswith different levels,one of the levels for

each categorical variable was consideredas a reference level in the estimation. Theeffects of the significant factors for park-ing lot crashes were studied by examiningthe odds ratios against the reference case.The location of the crashes was modeled

using an oversampled dataset; if the crashoccurred at a parking lot (public/private)the variable had a value of 1; otherwise, ithad a value of 0 (Model I). Using a sepa-rated dataset, crashes at public parkinglots were modeled considering a valueof 1 if the crash occurred at a publicparking lot (about 57 percent) and 0 if itoccurred at a private parking lot (ModelII). The places where anyone could parktheir vehicles were defined as public

parking lots, for example, at shoppingmalls. Private parking lots were the lotsowned by private entities, but did notinclude driveways of individual homes.

Model I: Parking Lot CrashCharacteristicsDriver characteristics

Four driver attributes were investigatedin this study: age, gender, race, and alco-hol/drug use. All of these characteristicsexcept alcohol/drug use were found to besignificant in the model.

Drivers were grouped by age in 10-year intervals. The propensity of driversother than young drivers (less than 26years old) to be involved in a crash ina parking lot increased with age. Rela-tive to drivers younger than 26 years old,the likelihood of a crash was highest forpeople older than 75 years (OR = 2.06),followed by the age group 6675 (OR =1.544), then the age group 5665 (OR =1.287). A study by Stamatiadis et al.5 alsofound that older drivers are overinvolved

in parking lot crashes. Non-white driv-ers of races other than Hispanic or blackhad a 19.5 percent higher chance of be-ing involved in a parking lot crash thanwhite drivers. This could also be relatedto tourists, who are common in Florida.The model showed that the likelihoodof crashes for Hispanic drivers was 23.4percent less than for white drivers. Thisoutcome indicates that the Hispanic driv-ers drive more carefully in parking lotsthan white drivers.


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The results showed that drivers genderhad a significant impact on the probabil-ity of parking lot crashes. Female driverswere about 23 percent more likely to beinvolved in these crashes than male driv-ers. Laapotti and Keskinen1 found thatthe odds of having a reversing/backed intocrash among female drivers were 1.4 timesthe odds among male drivers.

Use of alcohol and most drugs poten-tially decreases drivers decision-makingability and impairs vision. Also it reducesalertness and leads to mistakes that mayresult in crashes. Interestingly, this factorwas found to be insignificant at the 95percent confidence level when consideredas a covariate in the final model. How-ever, this factor was kept in the modelfor two reasons: A) the stepwise selectionprocedure in the logistic model buildingprocedure considered this factor to be

significant to be entered in the model evenat the 95 percent confidence level, and B)alcohol/drug influence has been widelyrecognized as an important risk factor forcrashes.4 Perhaps people driving under theinfluence of alcohol and/or drugs are toocareful at the beginning of the trip andtheir level of alertness decreases with time.

Road environment characteristicsThe effect of lighting conditions, visionobstruction, and weather conditions werefound significant for parking lot crashes.Crash propensity was 20.2 percent lowerduring dawn and dusk hours than duringdaytime. Crashes were more likely to oc-cur while drivers vision is obstructed bybuildings/fixed objects than when driversvision is not obstructed (OR = 5.802).Crash propensity was found to be about80.2 percent higher when vision is ob-

structed by some other parked/stoppedvehicle than when drivers vision is notobstructed. The possibility of a crashwhen vision is obstructed by trees/crops/bushes was found to be about 1.6 timeshigher than when vision is unobstructed.It was interesting to find that the oddsratio of crash propensity at parking lotsduring cloudy, rainy, or foggy weather

was lower than in clear/good weather.Perhaps people drive more cautiously ininclement weather.

Vehicle and crash characteristics

Among crash types, it was found that col-lision with a parked car and a crash whilereversing a vehicle had a higher likelihoodthan rear-end crashes; and they were fol-lowed by collision with pedestrian andcollision with fixed object (all cases rela-tive to the propensity of rear-end crashes).

(C) (d)

(b)(a)

Figure 1. Distribution of (a) types of crashes, (b) vehicle types, (c) age, and (d) lighting condition, involved in crashes at parking lots.


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Laapotti and Keskinen1 found that 70percent of all backed into or reversingcrashes between 1984 and 2000 tookplace in parking lots. The likelihood ofright-angle crashes was 4.4 times greaterthan that of rear-end crashes, while theoccurrence of left-angle crashes was 1.79

times higher than that of rear-end crashes.Only involvement of large vehicles (me-dium trucks, heavy trucks, and buses) wasfound significant at the 95 percent con-fidence level, with a 38.2 percent higherpossibility of crashes compared to thatof cars.

It was found that PDO crashes had thehighest likelihood in parking lots. Sincethe vehicles move at low speeds, greaterseverity is not expected in these types ofcrashes.

Model II: Crash Propensity atPublic Parking LotsSix variables were found significant inModel II at the 95 percent confidencelevel. These variables were race, lightingcondition, vehicle type, alcohol/drug use,injury severity, and crash type.

Black drivers were almost 24 percentless likely to be involved in crashes atpublic parking lots than white drivers.Crash propensity for Hispanic drivers wasabout 21 percent less than that of whitedrivers. Occurrence of crashes in publicparking lots of drivers under the influenceof drugs was about two times higher thanfor drivers who did not drink or use drugs.Drivers in public lots under the influenceof both alcohol and drugs were about 1.5times more likely to have a crash thandrivers who neither drank nor used drugs.Perhaps the restricted access to privateparking lots diminishes the likelihood ofalcohol and/or drug-related crashes. Pri-vate parking lots are also mostly utilized

during the working hours and workingdays, when alcohol is less often used.

Similar to the results from Model I, itwas found that daylight hours have highercrash propensities than any other hours.This is reasonable because parking lots aremostly used during day hours. Therefore,vehicular movement is light during nighthours, likely lowering crash probabilities.

Among vehicle types, vans had a 12.5percent higher crash propensity at publiclots than cars.

Crashes resulting in fatalities were notsignificant at the 95 percent confidencelevel compared to PDO crashes. This isexpected, due to low cruising speeds atparking lots. However, the possibility ofa crash in a public lot resulting in inju-ries was 11.4 percent higher than PDO

crashes, but this could be due to under-reporting of PDO crashes. According toModel II, propensities for the left-anglecrashes at public parking lots were foundto be 21.1 percent higher compared torear-end crashes, and the possibility wasabout 14 percent lower for right-anglecrashes than for rear-end crashes at publicparking lots. Crash propensity for colli-sion with fixed objects at public parkinglots was 23.1 percent lower than that ofrear-end crashes. Crash propensities for

collision with parked car and collisionwith pedestrian at public lots were lowerby about 14 percent and 16.3 percent,respectively, than that of rear-end crashes.

ConclusionThe main goal of this paper was to gainan insight into the risk factors influenc-ing crashes at parking lots. However, theanalysis did not consider physical char-acteristics of parking lots and parkingconfiguration due to the unavailabilityof data. For future studies, these factorscould be included in the model and ana-lyzed for better understanding of parkinglot crashes. The results can contribute tobetter parking area design and signage,and driver education and awareness.

References1. Laapotti, S. and E. Keskinen. Has the

Difference in Accident Patterns between Male

and Female Drivers Changed between 1984 and

2000?Accident Analysis and Prevention, Vol. 36

(2004): 577584.

2. Retting, R.A., A.F. Williams, D.F. Pre-usser, and H.B. Weinstein. Classifying Urban

Crashes for Countermeasure Development.Ac-

cident Analysis and Prevention, Vol. 27 (1995):

283294.

3. Tay, R., S.M. Rifaat, and H.C. Chin. A

Logistic Model of the Effect of Roadway, Envi-

ronment, Vehicle, Crash and Driver Character-

istics on Hit-and-Run Crashes.Accident Analysis

and Prevention, Vol. 40 (2008): 13301336.

4. Yan, X., E. Radwan, and M. Abdel-Aty.

Characteristics of Rear-End Accidents at Sig-

nalized Intersections Using Multiple Logistic

Regression Model.Accident Analysis and Preven-

tion, Vol. 37 (2005): 983995.

5. Stamatiadis, N., W.C. Taylor, and F.X.

Mckelvey. Older Drivers and Intersection Traf-

fic Control Device. Journal of Transportation

Engineering, Vol. 117, No. 3 (1991): 311319.

CHOWDHURY SIDDIQUI,

M.S., Ph.D. candidate, got

his masters from the Univer-

sity of Central Florida and is

currently working towards his

doctoral degree in the Trans-

portation Systems Engineering Track at the same

university. His research emphasis is in the areas of

traffic safety and transportation planning.

MOHAMED ABDEL-ATY,

P.E., Ph.D., is a professor of

transportation engineering

at the University of Central

Florida (UCF). He is the

program director of Safety

and Operations at the Center for Advanced

Transportation Systems Simulation at UCF. His

main expertise and interest is in the areas of traf-

fic safety, travel demand analysis, and ITS. Dr.

Abdel-Aty is a leading traffic safety expert at both

the national and international level. He has pub-

lished more than 275 papers (140 in journals).

In 2003 he was selected as UCFs Distinguished

Researcher and in 2007 as UCFs Outstanding

Graduate Teacher. Dr. Abdel-Aty is an Associate

Editor ofAccident Analysis and Prevention.

He is a member of the editorial board of theITS

Journal. He is a registered professional engineer

in Florida.

TAHERA ANJUMAN,

M.S., E.I.T., completed

her M.S. in transportation

engineering from ClemsonUniversity. Her research

interests are in ITS and

traffic operation. She holds a Lecturer position in

the Department of Civil Engineering at Stamford

University, Dhaka, Bangladesh.

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Parking Related Crash Characteristics (Article)