Pattern Recognition and Classification of Fatal Traffic Accidents in Israel: A Neural Network Approach

Journal of Transportation Safety and Security

Volumn 3, Issue 4, 2011, Pages 304-323

  Prato, Carlo Giacomo ^a   Gitelman, Victoria ^b   Bekhor, Shlomo ^b  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

accident factors; accident patterns; cluster analysis; feed forward back propagation neural networks; Kohonen networks

Indexed keywords

EID: 84859417001     PISSN: 19439962     EISSN: 19439970     Source Type: Journal    
DOI: 10.1080/19439962.2011.624291     Document Type: Article

References (39)

1. Aras, N., Oommen, B. J. and Altmel, I. K. 1999. The Kohonen network incorporating explicit statistics and its application to the Traveling Salesman Problem. Neural Networks, 12: 1273-1284.
2. Augen, J. 2004. Bioinformatics in the post-genomic era: Genome, transcriptome, proteome, and information-based medicine, Calgary, Canada: Addison-Wesley.
3. Avitzour, M. 2007. Injured pedestrians: Problem's scope, circumstances, injury profile and outcomes, Tel Aviv, Israel: Israel Center for Trauma and Emergency Medicine Research, Gertner Institute.
4. Ballesteros, M. F., Dischinger, P. C. and Langenberg, P. 2004. Pedestrian injuries and vehicle type in Maryland 1995-1999. Accident Analysis and Prevention, 36(1): 73-81.
5. Berg, H. Y., Gregersen, N. P. and Laflamme, L. 2004. Typical patterns in road-traffic accidents during driver training: an explorative Swedish national study. Accident Analysis and Prevention, 36(4): 603-608.
6. Burke, L. I. 1996. Neural methods for the travelling salesman problem: Insights from operations research. Neural Networks, 7: 681-690.
7. Chang, L. Y. and Chen, W. C. 2005. Data mining of tree-based models to analyze freeway accident frequency. Journal of Safety Research, 36(4): 365-375.
8. Cottrell, M. and Rousset, P. 1997. The Kohonen algorithm: a powerful tool for analyzing and representing quantitative and qualitative data. Lecture Notes in Computer Science, 1240: 861-871.
9. Eluru, N., Bhat, C. R. and Hensher, D. A. 2008. A mixed generalized ordered response model for examining pedestrian and bicyclist injury severity level in traffic crashes. Accident Analysis and Prevention, 40(3): 1033-1054.
10. Erwin, E., Obermayer, K. and Schulten, K. 1992. Self-organizing maps: ordering, convergence properties and energy functions. Biological Cybernetics, 67: 47-55.
11. Factor, R., Mahalel, D. and Yair, G. 2008. Inter-group differences in road-traffic crash involvement. Accident Analysis and Prevention, 40(6): 2000-2007.
12. Fleury, D. and Brenac, T. 2001. Accident prototypical scenarios, a tool for road safety research and diagnostic studies. Accident Analysis and Prevention, 33(2): 267-276.
13. Fontaine, H. and Gourlet, Y. 1997. Fatal pedestrian accidents in France: A typological analysis. Accident Analysis and Prevention, 29(3): 303-312.
14. Geurts, K., Thomas, I. and Wets, G. 2005. Understanding spatial concentrations of road accidents using frequent item sets. Accident Analysis and Prevention, 37(4): 787-799.
15. Geurts, K., Wets, G., Brijs, T. and Vanhoof, K. 2003. Profiling of high-frequency accident locations by use of association rules. Transportation Research Record, 1840: 123-130.
16. Gitelman, V., Balasha, D., Carmel, R., Hendel, L. and Pesahov, F. 2012. Characterization of pedestrian accidents and an examination of infrastructure measures to improve pedestrian safety in Israel. Accident Analysis and Prevention, 44(1): 63-73
17. Harruff, R., Avery, A. and Alter-Pandya, A. 1998. Analysis of circumstances and injuries in 217 pedestrian traffic fatalities. Accident Analysis and Prevention, 30(1): 11-20.
18. Hasselberg, M., Vaez, M. and Laflamme, L. 2005. Socioeconomic aspects of the circumstances and consequences of car crashes among young adults. Social Science and Medicine, 60(2): 287-295.
19. Kohonen, T. 1982. Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43: 59-69.
20. Kohonen, T. 2001. Self-organizing maps, 3rd extended ed., Berlin & Heidelberg, Germany: Springer Verlag.
21. Laapotti, S. and Keskinen, E. 2004. Has the difference in accident patterns between male and female drivers changed between 1984 and 2000?. Accident Analysis and Prevention, 36(4): 577-584.
22. Milton, J. C., Shankar, V. N. and Mannering, F. L. 2008. Highway accident severities and the mixed logit model: An exploratory empirical analysis. Accident Analysis and Prevention, 40(1): 260-266.
23. Organization for Economic Co-operation and Development. 2008. Towards zero: Ambitious road safety targets and the safe system approach, Paris, France: OECD Publishing, International Transport Forum of the Organization for Economic Co-operation and Development.
24. Peleg, K. and Aharonson-Daniel, L. 2004. Road traffic accidents - severe injuries. How missing data can impair decision making?. Harefuah, 143(2): 111-115
25. Prato, C. G., Gitelman, V. and Bekhor, S. 2012. Mapping patterns of pedestrian fatal accidents in Israel. Accident Analysis and Prevention, 44(1): 56-62
26. Prato, C. G., Toledo, T., Lotan, T. and Taubman Ben-Ari, O. 2010. Modeling the behavior of novice young drivers during the first year after licensure. Accident Analysis and Prevention, 42(2): 480-486.
27. Preusser, D. F., Williams, A. F. and Ulmer, R. G. 1995. Analysis of fatal motorcycle crashes: crash typing. Accident Analysis and Prevention, 27(6): 845-851.
28. Reed, R. D. and Marks, R. J. 1999. Neural smithing: Supervised learning in feedforward artificial neural networks, Cambridge, MA: MIT Press.
29. Retting, R. A., Williams, A. F., Preusser, D. F. and Weinstein, H. B. 1995. Classifying urban crashes for countermeasure development. Accident Analysis and Prevention, 27(3): 283-294.
30. Retting, R. A., Williams, J. and Schwartz, S. I. 2000. Motor vehicle crashes on bridges and countermeasure opportunities. Journal of Safety Research, 31(4): 203-210.
31. Ritter, H. and Schulten, K. 1988. Convergence properties of Kohonen's topology conserving maps: fluctuations, stability and dimension selection. Biological Cybernetics, 60: 59-71.
32. Sivak, M. and Schoettle, B. 2010. Toward understanding the recent large reductions in U.S. road fatalities. Traffic Injury Prevention, 11(6): 561-566.
33. Skyving, M., Berg, H. Y. and Laflamme, L. 2009. A pattern analysis of traffic crashes fatal to older drivers. Accident Analysis and Prevention, 41(2): 253-258.
34. SPSS Inc. 2007. Clementine® 12.0 user's guide, Chicago, IL: Integral Solutions Limited.
35. Tseng, W. S., Nguyen, H., Liebowitz, J. and Agresti, W. 2005. Distractions and motor vehicle accidents: data mining application on fatality analysis reporting system (FARS) data files. Industrial Management and Data Systems, 105(9): 1188-1205.
36. Yan, X. and Radwan, E. 2006. Analyses of rear-end crashes based on classification tree models. Traffic Injury Prevention, 7(3): 276-282.
37. Wang, Y., Hasselberg, M., Wu, Z. and Laflamme, L. 2008. Distribution and characteristics of road traffic crashes in the Chaoyang District of Beijing. Accident Analysis and Prevention, 40(1): 334-340.
38. Wegman, F. and Aarts, L. 2006. Advancing sustainable safety: National road safety outlook for 2005-2020, Leidschendam, The Netherlands: SWOW Institute for Safety Research.
39. Zegeer, C. V., Stutts, J. C., Huang, H., Zhou, M. and Rodgman, E. 1993. Analysis of elderly pedestrian accidents and recommended countermeasures. Transportation Research Record, 1405: 56-63.