A clustering regression approach: A comprehensive injury severity analysis of pedestrian-vehicle crashes in New York, US and Montreal, Canada

Safety Science

Volumn 54, Issue , 2013, Pages 27-37

  Mohamed, Mohamed Gomaa ^a   Saunier, Nicolas ^a   Miranda Moreno, Luis F ^b   Ukkusuri, Satish V ^c  

^a ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c PURDUE UNIVERSITY   (United States)

Author keywords

Built environmental; Clustering injury severity; Contributing factors; Latent class; Pedestrian safety; Pedestrian driver characteristics

Indexed keywords

BUILT ENVIRONMENTAL; CONTRIBUTING FACTOR; INJURY SEVERITY; LATENT CLASS; PEDESTRIAN-DRIVER CHARACTERISTICS;

ACCIDENTS;

PEDESTRIAN SAFETY;

ACCIDENTAL INJURY; ARTICLE; CANADA; CLUSTER ANALYSIS; ENVIRONMENTAL FACTOR; FATALITY; INJURY SEVERITY; MATHEMATICAL MODEL; PEDESTRIAN; PRIORITY JOURNAL; REGRESSION ANALYSIS; SOCIAL STATUS; TRAFFIC ACCIDENT; TRAFFIC SAFETY; UNITED STATES;

EID: 84871374921     PISSN: 09257535     EISSN: 18791042     Source Type: Journal    
DOI: 10.1016/j.ssci.2012.11.001     Document Type: Article

References (21)

1. Aziz, H., Ukkusuri, S.V., Hasan, S., Exploring the determinants of pedestrian-vehicle crash severity in New York City. Accid. Anal. Prev. (2012), in press doi:10.1016/j.aap.2012.09.034.
2. Berkhin, P., 2002. Survey of clustering data mining techniques. Available online: (last visit: 26 Nov. 2012). http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.3739.
3. Borooah V.K. Logit and Probit: Ordered and Multinomial Models 2002, Sage Publication, Thousand Oaks, CA.
4. Chang L.-Y., Wang H.-W. Analysis of traffic injury severity: an application of non-parametric classification tree techniques. Accident Analysis and Prevention 2006, 38:1019-1027.
5. Clifton K.J., Burnier C.V., Akar G. Severity of injury resulting from pedestrian-vehicle crashes: what can we learn from examining the built environment?. Transportation Research Part D: Transport and Environment 2009, 14:425-436.
6. Depaire B., Wets G., Vanhoof K. Traffic accident segmentation by means of latent class clustering. Accident Analysis and Prevention 2008, 40:1257-1266.
7. Eluru N., Bagheri M., Miranda-Moreno L.F., Fu L. A latent class modeling approach for identifying vehicle driver injury severity factors at highway-railway crossings. Accident Analysis and Prevention 2012, 47:119-127.
8. Eluru N., Bhat C.R., Hensher D.A. A mixed generalized ordered response model for examining pedestrian and bicyclist injury severity level in traffic crashes. Accident Analysis and Prevention 2008, 40:1033-1054.
9. Jackman, S., 2000. Models for ordered outcomes. Political Science 200C.
10. Kim K., Yamashita E.Y. Using a k-means clustering algorithm to examine patterns of pedestrian involved crashes in Honolulu, Hawaii. Journal of Advanced Transportation 2007, 41:69-89.
11. Kuhnert P.M., Do K.-A., McClure R. Combining non-parametric models with logistic regression: an application to motor vehicle injury data. Computational Statistics and Data Analysis 2000, 34:371-386.
12. Lee C., Abdel-Aty M. Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accident Analysis and Prevention 2005, 37:775-786.
13. Prato, C.G., Bekhor, S., Galtzur, A.M., D., Prashker, J.N., 2010. Exploring the potential of data mining techniques for the analysis of accident patterns. In: 12th WCTR, Lisbon, Portugal.
14. Sze N.N., Wong S.C. Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes. Accident Analysis and Prevention 2007, 39:1267-1278.
15. Tay R., Choi J., Kattan L., Khan A. A multinomial logit model of pedestrian-vehicle crash severity. International Journal of Sustainable Transportation 2011, 5:233-249.
16. Ukkusuri S.V., Miranda-Moreno L.F., Ramadurai G., Isa-Tavarez J. The role of built environment on pedestrian crash frequency. Safety Science 2012, 50:1141-1151.
17. Vermunt J.K., Magidson J. Latent Class Cluster Analysis. Applied Latent Class Analysis 2002, Cambridge University Press, Cambridge.
18. Washington S., Karlaftis M., Mannering F. Statistical and econometric methods for transportation data analysis 2010, CRC Press/Routledge. second ed.
19. Xu R., Wunsch D. Survey of clustering algorithms. IEEE Transactions on Neural Networks 2005, 16:645-678.
20. Yau K.K.W. Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong. Accident Analysis and Prevention 2004, 36:333-340.
21. Zahabi S., Strauss J., Manaugh K., Miranda-Moreno L. Estimating potential effect of speed limits, built environment, and other factors on severity of pedestrian and cyclist injuries in crashes. Transportation Research Record: Journal of the Transportation Research Board 2011, 2247:81-90.