Aggregate nonparametric safety analysis of traffic zones

Accident Analysis and Prevention

Volumn 45, Issue , 2012, Pages 317-325

  Siddiqui, Chowdhury ^a   Abdel Aty, Mohamed ^a   Huang, Helai ^b  

^a University of Central Florida   (United States)

^b CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Data mining; Macro level safety analysis; Random forest; Safety planning; Severe crash; Total crash

Indexed keywords

MACRO-LEVEL SAFETY ANALYSIS; RANDOM FORESTS; SAFETY PLANNING; SEVERE CRASH; TOTAL CRASH;

DATA MINING; DECISION TREES; FORESTRY; MINE TRUCKS; SECURITY SYSTEMS; SPEED; TRAFFIC CONTROL; TRUCKS;

AIRCRAFT ACCIDENTS;

FORESTRY; FORESTS; TRUCKS; VELOCITY;

ACCELERATION; ARTICLE; DATA MINING; DECISION TREE; ENGINEERING; ENVIRONMENTAL PLANNING; HUMAN; METHODOLOGY; NONPARAMETRIC TEST; RISK ASSESSMENT; SAFETY; STATISTICS; TRAFFIC ACCIDENT; UNITED STATES;

ACCELERATION; ACCIDENTS, TRAFFIC; DATA MINING; DECISION TREES; ENGINEERING; ENVIRONMENT DESIGN; FLORIDA; HUMANS; RISK ASSESSMENT; SAFETY; STATISTICS, NONPARAMETRIC;

EID: 84856112825     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2011.07.019     Document Type: Article

References (40)

1. M. Abdel-Aty, J. Keller, and P.A. Brady Analysis of types of crashes at signalized intersections by using complete crash data and tree-based regression Transportation Research Record 1908 2005 37 45
2. M. Abdel-Aty, A. Pande, A. Das, and W.J. Knibbe Assessing safety on Dutch freeway with data from infrastructure-based intelligent transportation systems Transportation Research Record 2083 2008 153 161
3. J. Aguero-Valverde, and P.P. Jovanis Spatial analysis of fatal and injury crashes in Pennsylvania Accident Analysis and Prevention 38 2006 618 625
4. E. Amoros, and L.M. Laumon Comparison of road crashes incidence and severity between some French counties Accident Analysis and Prevention 35 2003 537 547
5. ArcMap, Version 9.2, Environmental Systems Research Institute (ESRI) Inc.
6. L. Breiman, J. Friedman, R. Olshen, and C. Stone Classification and Regression Trees 1984 Wadsworth International Group Belmont, CA
7. Breiman, L.; Cutler, A.; 2010. Random forests. http://www.stat.berkeley. edu/∼breiman/RandomForests/cc-home.htm (accessed 31.03.10).
8. L.-Y. Chang, and W.-C. Chen Data mining of tree-based models to analyze freeway accident frequency Journal of Safety Research 36 2005 365 375
9. L.-Y. Chang, and H.-W. Wang Analysis of traffic injury severity: an application of non-parametric classification tree techniques Accident Analysis and Prevention 38 2006 1019 1027
10. Elvik, R.; Christensen, P.; Amundsen, A.; 2004. Speed and Road Accidents. An Evaluation of the Power Model. TØI report 740/2004. Institute of Transport Economics TOI, Oslo.
11. F.L.D. Guevara, S.P. Washington, and J. Oh Forecasting crashes at the planning level: simultaneous negative binomial crash model applied in Tucson, Arizona Transportation Research Record 1897 2004 191 199
12. A. Hadayeghi, A.S. Shalaby, and B.N. Persaud Macrolevel accident prediction models for evaluating safety of urban transportation systems Transportation Research Record 1840 2003 87 95
13. A. Hadayeghi, A.S. Shalaby, B.N. Persaud, and C. Cheung Temporal transferability and updating of zonal level accident prediction models Accident Analysis and Prevention 38 2006 579 589
14. R. Harb, X. Yan, E. Radwan, and X. Su Exploring precrash maneuvers using classification trees and random forests Accident Analysis and Prevention 41 2009 98 107
15. H. Huang, M. Abdel-Aty, and A. Darwiche County-level crash risk analysis in Florida: Bayesian spatial modeling Transportation Research Record 2148 2010 27 37
16. M.G. Karlaftis, and A.P. Tarko Heterogeneity considerations in accident modeling Accident Analysis and Prevention 30 1998 425 433
17. M.G. Karlaftis, and I. Golias Effects of road geometry and traffic volume on rural roadway accident rates Accident Analysis and Prevention 34 2002 357 365
18. Kloeden, C.N.; McLean, A.J.; Glonek, G.; 2002. Reanalysis of Travelling Speed and the Rate of Crash Involvement in Adelaide South Australia. Report No. CR 207. Australian Transport Safety Bureau ATSB, Civic Square, ACT.
19. N. Levine, K.E. Kim, and L.H. Nitz Spatial analysis of Honolulu motor vehicle crashes: II zonal generators Accident Analysis and Prevention 27 1995 675 685
20. H.J. Miller, and S.-L. Shaw Geographic Information System for Transportation, Principles and Applications 2001 Oxford University Press
21. A. Naderan, and J. Shahi Aggregate crash prediction models: introducing crash generation concept Accident Analysis and Prevention 42 2010 339 346
22. National Transportation Laboratory, U.S. Department of Transportation. An Introduction to Urban Travel Demand Forecasting - A Self Instructional Text. http://ntl.bts.gov/DOCS/UT.html (accessed 8.06.11).
23. R.B. Noland Traffic fatalities and injuries: the effect of changes in infrastructure and other trends Accident Analysis and Prevention 35 2003 599 611
24. R.B. Noland, and L. Oh The effect of infrastructure and demographic change on traffic-related fatalities and crashes: a case study of Illinois county-level data Accident Analysis and Prevention 36 2004 525 532
25. R.B. Noland, and M.A.A. Quddus Spatially disaggregate analysis of road casualties in England Accident Analysis and Prevention 36 2004 973 984
26. A. Peters, and H. MacDonald Unlocking the Census with GIS 2004 ESRI Publication
27. X. Qin, and J. Han Variable selection issues in tree-based regression models Transportation Research Record 2061 2008 30 38
28. M.A. Quddus Modelling area-wide count outcomes with spatial correlation and heterogeneity: an analysis of London crash data Accident Analysis and Prevention 40 2008 1486 1497
29. SAS Software, Version 9.1.3 Service Pack 3. SAS Institute Inc.; Cary, NC, USA.
30. J.R. Stewart Application of classification and regression tree methods in roadway safety studies Transportation Research Record 1542 1996 1 5
31. Tignor, S.C.; Warren, D.; 1990. Driver Speed Behavior on U.S. Streets and Highways. 1990 Compendium of Technical Papers. Institute of Transportation Engineers, Washington, DC. http://www.ibiblio.org/rdu/sl-irre0.html (accessed 2.06.10).
32. The R Project for Statistical Computing. http://www.r-project.org/ (accessed 13.02.10).
33. U.S. Census Bureau. http://www.census.gov/geo/www/cob/tz-metadata.html (accessed 13.02.09).
34. S. Washington Iteratively specified tree-based regression: theory and trip generation example Journal of Transportation Engineering 126 2000 482 491
35. Washington, S.; Schalkwyk, I. V.; Mitra, S.; Meyer, M.; Dumbaugh, E.; Zoll, M.; 2006. Incorporating Safety into Long-range Transportation Planning. NCHRP Report 546. Transportation Research Board of the National Academics, Washington, DC.
36. Washington, S.; Schalkwyk, I.V.; You, D.; Shin, K.; Samuelson, J.P.; 2010. PLANSAFE: Forecasting the Safety Impacts of Socio-demographic Changes and Safety Countermeasures. Report No. NCHRP 8-44(2). Transportation Research Board, Washington, DC.
37. M. Wier, J. Weintraub, E.H. Humphreys, E. Seto, and R. Bhatia An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning Accident Analysis and Prevention 41 2009 137 145
38. X. Yan, and E. Radwan Analyses of rear-end crashes based on classification tree models Traffic Injury Prevention 7 2006 276 282
39. X. Yan, S. Richards, and X. Su Using hierarchical tree-based regression model to predict train-vehicle crashes at passive highway-rail grade crossings Accident Analysis and Prevention 42 2010 64 74
40. J. You, Z. Nedović-Budić, and T.J. Kim A GIS-based traffic analysis zone design: technique Transportation Planning and Technology 21 1997 45 68