Road crashes not only claim lives and inflict injuries but also create an economic burden on society because of lost productivity. Many studies have identified factors affecting the frequency and severity of crashes. However, few, if any, studies have explored the effect of street pattern on injury risks in urban crashes. In this study, street pattern or urban form is classified into four categories: gridiron, warped parallel, loops and lollipops, and mixed patterns. Their effects on injury risk are examined together with other factors including road features, drivers’ characteristics, crash characteristics, environmental conditions, and vehicle attributes. Calgary, Alberta, Canada, is chosen as the case study, and the logistic regression model is applied with reported crash data from 2003 to 2005 to investigate various factors. The results suggest that current popular patterns, including the loops and lollipops design, are safer than the conventional gridiron pattern from an injury risk perspective in the event of a crash.
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References
1.
PedenM., ScurfieldR., SleetD., MohanD., JarawanE., and MathersC.World Report on Road Traffic Injury Prevention.World Health Organization, Geneva, 2004.
2.
Canadian Motor Vehicle Traffic Collision Statistics: 2006.Transport Canada, Ottawa, Ontario, 2007.
3.
KrullK. A., KhattakA. J., and CouncilF. M.Injury Effects of Rollovers and Events Sequence in Single-Vehicle Crashes. In Transportation Research Record: Journal of the Transportation Research Board, No. 1717, TRB, National Research Council, Washington, D.C., 2000, pp. 46–54.
4.
LeeJ., and ManneringF.Impact of Roadside Features on the Frequency and Severity of Run-off-Roadway Accidents: An Empirical Analysis.Accident Analysis and Prevention, Vol. 34, No. 2, 2002, pp. 149–161.
5.
YamamotoT., and ShankarV. N.Bivariate Ordered-Response Probit Model of Driver's and Passenger's Injury Severities in Collision with Fixed Objects. Presented at 81st Annual Meeting of the Transportation Research Board, Washington, D.C., 2002.
6.
EvansL., and FrickM. C.Mass Ratio and Relative Driver Fatality Risk in Two-Vehicle Crashes.Accident Analysis and Prevention, Vol. 25, No. 2, 1993, pp. 213–224.
7.
EvansL., and FrickM. C.Car Mass and Fatality Risk: Has the Relationship Changed?American Journal of Public Health, Vol. 84, 1994, pp. 33–36.
8.
DuncanC. S., KhattakA. J., and CouncilF. M.Applying the Ordered Probit Model to Injury Severity in Truck–Passenger Car Rear-End Collisions. In Transportation Research Record 1635, TRB, National Research Council, Washington, D.C., 1998, pp. 63–71.
9.
ShankarV., and ManneringF.An Exploratory Multinomial Logit Analysis of Single-Vehicle Motorcycle Accident Severity.Journal of Safety Research, Vol. 27, No. 3, 1996, pp. 183–194.
10.
QuddusM. A., NolandR. B., and ChinH. C.An Analysis of Motorcycle Injury and Vehicle Damage Severity Using Ordered Probit Model.Journal of Safety Research, Vol. 33, No. 4, 2002, pp. 445–462.
11.
UlfarssonG. F., and ManneringF. L.Difference in Male and Female Injury Severities in Sport Utility Vehicle, Minivan, Pickup and Passenger Car Accidents.Accident Analysis and Prevention, Vol. 36, No. 2, 2004, pp. 135–147.
12.
ZhangJ., LindsayJ., ClarkeK., RobbinsG., and MaoY.Factors Affecting the Severity of Motor Vehicle Traffic Crashes Involving Elderly Drivers in Ontario.Accident Analysis and Prevention, Vol. 32, No. 1, 2000, pp. 117–125.
13.
BedardM., GuyattG. H., StonesM. J., and HirdesJ. P.The Independent Contribution of Driver, Crash, and Vehicle Characteristics to Driver Fatalities.Accident Analysis and Prevention, Vol. 34, No. 6, 2002, pp. 717–727.
14.
DissanayakeS., and LuJ.Analysis of Severity of Young Driver Crashes: Sequential Binary Logistic Regression Modeling. In Transportation Research Record: Journal of the Transportation Research Board, No. 1784, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 108–114.
15.
DissanayakeS., and LuJ. J.Factors Influential in Making an Injury Severity Difference to Older Drivers Involved in Fixed Object–Passenger Car Crashes.Accident Analysis and Prevention, Vol. 34, No. 5, 2002, pp. 609–618.
16.
ZajacS. S., and IvanJ. N.Factors Influencing Injury Severity of Motor Vehicle Crossing Pedestrian Crashes in Rural Connecticut.Accident Analysis and Prevention, Vol. 35, No. 3, 2003, pp. 369–379.
17.
KeallM. D., FrithW. J., and PattersonT. L.The Influence of Alcohol, Age and Number of Passengers on the Nighttime Risk of Driver Fatal Injury in New Zealand.Accident Analysis and Prevention, Vol. 36, No. 1, 2004, pp. 49–61.
18.
ValentF., SchiavaF., SavonittoC., GalloT., BrusaferroS., and BarboneF.Risk Factors for Fatal Road Traffic Accidents in Udine, Italy.Accident Analysis and Prevention, Vol. 34, No. 1, 2002, pp. 71–84.
19.
WolfeC. R.Streets Regulating Neighborhood Form: A Selective History. In Public Streets for Public Use (MoudonA. V., ed.), Columbia University Press, New York, 1987.
20.
SouthworthM., and Ben-JosephE.Street Standards and the Shaping of Suburbia.Journal of the American Planning Association, Vol. 61, No. 1, 1995, pp. 65–81.
21.
MarksH.Subdividing for Traffic Safety.Traffic Quarterly, Vol. 11, No. 3, 1957, pp. 308–325.
22.
SouthworthM., and Ben-JosephE.Streets and the Shaping of Towns and Cities.Island Press, Washington, D.C., 2003.
23.
TayR., RifaatS. M., and ChinH. C.A Logistic Model of the Effects of Roadway, Environmental, Vehicle, Crash and Driver Characteristics on Hit-and-Run Crashes.Accident Analysis and Prevention, Vol. 40, No. 4, 2008, pp. 1330–1336.
24.
JonesI. S., and WhitfieldR. A.Predicting Injury Risk and Risk-Taking Behaviour Among Young Drivers.Accident Analysis and Prevention, Vol. 20, No. 6, 1988, pp. 411–419.
25.
LuiK.-J., McGeeD., RhodesP., and PollockD.An Application of a Conditional Logistic Regression to Study the Effects of Safety Belts, Principal Impact Points, and Car Weights on Drivers’ Fatalities.Journal of Safety Research, Vol. 19, No. 4, 1988, pp. 197–203.
26.
TayR., BaruaU., and KattanL.Factors Contributing to Hit-and-Run in Fatal Crashes.Accident Analysis and Prevention, Vol. 41, No. 2, 2009, pp. 227–233.
27.
SimoncicM.Road Fatalities in Slovenia Involving a Pedestrian, Cyclist or Motorcyclist and a Car.Accident Analysis and Prevention, Vol. 33, No. 2, 2001, pp. 147–156.
28.
KimJ., KimS., UlfarssonG., and PorrelloL.Bicyclist Injury Severities in Bicycle–Motor Vehicle Accidents.Accident Analysis and Prevention, Vol. 39, No. 2, 2007, pp. 238–251.
29.
PeltzmanS.The Effects of Automobile Safety Regulation.Journal of Political Economy, Vol. 83, 1975, pp. 677–726.
30.
StreffF. M., and GellerE. S.An Experimental Test of Risk Compensation: Between Subject Versus Within Subject Analyses.Accident Analysis and Prevention, Vol. 20, No. 4, 1988, pp. 277–287.
31.
TayR., and ChurchillA.The Effects of Different Types of Barriers on Traffic Speed.Canadian Journal of Transportation, Vol. 1, No. 1, 2007, pp. 56–66.
32.
McCarthyP., and TalleyW.Evidence on Risk Compensation and Safety Behaviour.Economic Letters, Vol. 62, 1999, pp. 91–96.
33.
TayR.Ageing Drivers: Storm in a Teacup?Accident Analysis and Prevention, Vol. 38, No. 1, 2006, pp. 112–121.
34.
WildeG. J. S.Target Risk.PDE Publications, Toronto, Ontario, Canada, 1994.
35.
RifaatS. M., and ChinH. C.Accident Severity Analysis Using Ordered Probit Model.Journal of Advanced Transportation, Vol. 41, No. 1, 2007, pp. 91–114.
36.
TayR., and RifaatS. M.Factors Contributing to the Severity of Intersection Crashes.Journal of Advanced Transportation, Vol. 41, No. 3, 2007, pp. 245–265.
37.
ChangL.-Y., and ManneringF. L.Predicting Vehicle Occupancies from Accident Data: An Accident Severity Approach. In Transportation Research Record 1635, TRB, National Research Council, Washington, D.C., 1998, pp. 93–104.
38.
KockelmanK. M., and KweonY.-J.Driver Injury Severity: An Application of Ordered Probit Models.Accident Analysis and Prevention, Vol. 34, No. 3, 2002, pp. 313–321.
39.
OuyangY., ShankarV., and YamamotoT.Modeling the Simultaneity in Injury Causation in Multivehicle Collisions. In Transportation Research Record: Journal of the Transportation Research Board, No. 1784, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 143–152.
40.
KimK., LiL., RichardsonJ., and NitzL.Drivers at Fault: Influences of Age, Sex, and Vehicle Type.Journal of Safety Research, Vol. 29, No. 3, 1998, pp. 171–179.
41.
Fatality Analysis Reporting System (FARS) Web-Based Encyclopedia.NHTSA, U.S. Department of Transportation, Washington, D.C.www-fars.nhtsa.dot.gov.
42.
BakerS. P., BraverE. R., ChenL.-H., LiG., and WilliamsA. F.Drinking Histories of Fatally Injured Drivers.Injury Prevention, Vol. 8, No. 3, 2002, pp. 221–226.
43.
LeeC., and Abdel-AtyM.Comprehensive Analysis of Vehicle–Pedestrian Crashes at Intersections in Florida.Accident Analysis and Prevention, Vol. 37, No. 4, 2005, pp. 775–786.
44.
DumbaughE.Safe Streets, Livable Streets.Journal of the American Planning Association, Vol. 71, No. 3, 2005, pp. 283–298.
