An ordered, discrete outcome model that relates the severity of injury suffered by a struck pedestrian to the speed of the striking vehicle is derived and then fit to previously published data. Particular care is taken to account for covariate measurement error and for the fact that the data were collected using an outcome-based, or retrospective, sampling plan. The results show similar patterns for children (ages 0–14) and adults (ages 15–59), but for elderly pedestrians (ages 60+) the injuries produced in crashes that involved lower impact speeds tended to be more severe than for the other two groups. Use of the model is illustrated by applying it to two reconstructed vehicle-pedestrian crashes to determine the likely severity of the injury had the driver adhered to a speed limit. Some implications for speed limits on residential streets are also pointed out.
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References
1.
Traffic Engineering Manual. Minnesota Department of Transportation, St. Paul, 1996.
2.
Special Report 254: Managing Speed. TRB, National Research Council, Washington, D.C., 1998.
3.
TignorS., and WarrenD.Driver Speed Behavior on U.S. Streets and Highways. Compendium of Technical Papers. Institute of Transportation Engineers, Washington, D.C., 1990.
4.
KloedenC., McLeanA., MooreV., and PonteG.Traveling Speed and the Risk of Crash Involvement. NHMRC Road Accident Research Unit, University of Adelaide, Adelaide, Australia, 1997.
5.
LaveC.Speeding, Coordination, and the 55-mph Speed Limit. American Economic Review, Vol. 75, 1985, pp. 1159–1164.
6.
WalzF., HoefligerM., and FehlmannW.Speed Limit Reduction from 60 to 50 km/h and Pedestrian Injuries. Proc., 27th Stapp Car Crash Conference. Society of Automotive Engineers, 1983, pp. 311–318.
7.
HomburgerW., and KellJ.Fundamentals of Traffic Engineering, 12th ed.Institute of Transportation Studies, University of California, Berkeley, 1988.
8.
RoeseN., and OlsonJ.What Might Have Been: The Social Psychology of Counterfactual Thinking. Lawrence Erlbaum Associates, Mahwah, N.J., 1995.
9.
LewisD.Philosophical Papers, Vol. II. Oxford University Press, New York, 1986.
10.
PearlJ.Causality: Models, Reasoning and Inference. Cambridge University Press, Cambridge, United Kingdom, 2000.
11.
PasanenE., and SalmivaaraH.Driving Speed and Pedestrian Safety in the City of Helsinki. Traffic Engineering and Control, Vol. 34, No. 6, 1993, pp. 308–310.
12.
AndersonR., McLeanA., FarmerM., LeeB., and BrooksC.Vehicle Travel Speeds and the Incidence of Fatal Pedestrian Crashes. Accident Analysis and Prevention, Vol. 29, 1997, pp. 667–674.
13.
AmemiyaT.Advanced Econometrics. Harvard University Press, Cambridge, Mass., 1985.
14.
VileniusA., RyanG., KloedenC., McLeanA., and DolinisJ.A Method of Estimating Linear and Angular Accelerations in Head Impacts to Pedestrians. Accident Analysis and Prevention, Vol. 26, 1994, pp. 563–570.
15.
WoodD.Impact and Movement of Pedestrians in Frontal Collisions with Vehicles. Proc., Institute of Mechanical Engineers, Vol. 202, No. D2, 1988, pp. 101–110.
16.
TharpK., and TsongasN.Injury Severity Factors—Traffic Pedestrian Collisions. SAE Technical Paper 770093. SAE, Inc., Warrendale, Pa., 1977.
17.
PasanenE.Driving Speeds and Pedestrian Safety: A Mathematical Model. National Technical Information Service Document PB93-141018. Department of Commerce, Washington, D.C., 1992.
18.
MacLaughlinT., WiechelJ., and GuentherD.Head Impact Reconstruction—HIC Validation and Pedestrian Injury Risk. SAE Technical Paper 930895. SAE Inc., Warrendale, Pa., 1993.
19.
LawrasonG., SwiercinskyR., and MasonR.Pedestrian Injury Causation Study. National Highway Traffic Safety Administration Report DOT-HS-7-01580. Department of Transportation, 1980.
20.
ManskiC., and LermanS.The Estimation of Choice Probabilities from Choice Based Sample. Econometrica, Vol. 45, 1977, pp. 1977–1988.
21.
PrenticeR., and PykeR.Logistic Disease Incidence Models and Case-Control Studies. Biometrika, Vol. 66, 1979, pp. 403–411.
22.
HsiehD., ManskiC.., and McFaddenD.Estimation of Response Probabilities from Augmented Retrospective Observations. Journal of American Statistical Association, Vol. 80, 1985, pp. 651–662.
23.
AshtonS.A Preliminary Assessment of the Potential for Pedestrian Injury Reduction Through Vehicle Design. Proc., 24th Stapp Car Crash Conference. SAE, Inc, Warrendale, Pa., 1982, pp. 609–635.
24.
AshtonS., PeddarJ., and MackayG.Pedestrian Injuries and the Car Exterior. SAE Technical Paper 770092. SAE, Inc., Warrendale, Pa., 1977.
25.
NiedererP.The Accuracy and Reliability of Accident Reconstruction. In Automotive Engineering and Litigation, Vol. 4 (PetersG. and PetersB., eds.). Wiley and Sons, N.Y., 1991, pp. 257–303.
26.
CarrollD., RuppertD., and StefanskiL.Measurement Error in Nonlinear Models. Chapman and Hall, London, United Kingdom, 1995.
27.
ArmstrongB.The Effects of Measurement Errors on Relative Risk Regressions. American Journal of Epidemiology, Vol. 132, 1990, pp. 1176–1184.
HauerE.The Safety of Older Persons at Intersections. In Special Report 218: Transportation in an Aging Society: Improving Mobility and Safety for Older Persons, Vol. 2, TRB, National Research Council, Washington, D.C., 1988, pp. 194–252.
30.
KnoblauchR.Causative Factors and Countermeasures for Rural and Suburban Pedestrian Accidents: Accident Data Collection and Analysis. National Highway Traffic Safety Administration Report DOT-HS-355-3-728. Department of Transportation, 1977.
31.
DavisG. A.Method for Estimating the Effect of Traffic Volume and Speed on Pedestrian Safety for Residential Streets. In Transportation Research Record 1636, TRB, National Research Council, 1998, pp. 110–115.
32.
DavisG.Vehicle/Pedestrian Collision Model for Neighborhood Traffic Control. Report to Minnesota Department of Transportation, St. Paul, 2001.
