Risk analysis of animal–vehicle crashes: a hierarchical Bayesian approach to spatial modelling

International Journal of Crashworthiness

Volumn 21, Issue 6, 2016, Pages 614-626

  Murphy, Andrew ^a  

^a Cecilia)   (Australia)

Author keywords

Animal vehicle crashes; hierarchical Bayesian model; Markov chain Monte Carlo (MCMC) techniques; multivariate Poisson lognormal regression model; road safety; spatial modelling

Indexed keywords

ACCIDENTS; ANIMALS; BAYESIAN NETWORKS; CODES (SYMBOLS); CRASHWORTHINESS; HIGHWAY ACCIDENTS; LAND USE; MARKOV PROCESSES; MONTE CARLO METHODS; MOTOR TRANSPORTATION; REGRESSION ANALYSIS; RISK ANALYSIS; ROADS AND STREETS; ROADSIDES; TRANSPORTATION; VEGETATION; VEHICLES;

HIERARCHICAL BAYESIAN MODELING; MARKOV CHAIN MONTE CARLO; POISSON LOGNORMAL REGRESSIONS; ROAD SAFETY; SPATIAL MODELLING; VEHICLE CRASHES;

RISK ASSESSMENT;

EID: 84990923227     PISSN: 13588265     EISSN: 17542111     Source Type: Journal    
DOI: 10.1080/13588265.2016.1209823     Document Type: Article

References (47)

1. M.A.Abdel-Aty and A.E.Radwan, Modeling traffic accident occurrence and involvement, Accid. Anal. Prev. 32 (2000), pp. 633–642.
2. J.Aguero-Valverde, Direct spatial correlation in crash frequency, 3rd International Conference on Road Safety and Simulation, Indianapolis, IN, 2011.
3. J.Aguero-Valverde and P.P.Jovanis, Spatial analysis of fatal and injury crashes in Pennsylvania, Accid. Anal. Prev. 38 (2006), pp. 618–625. Available at http://www.sciencedirect.com/science/article/B6V5S-4J5C7V9-1/2/cd7e658d3843299d8bfdb213567e0446.
4. S.Banerjee, B.P.Carlin, and A.E.Gelfand, Hierarchical Modeling and Analysis for Spatial Data, CRC Press, Boca Raton, 2003.
5. A.P.Clevenger, B.Chruszcz, and K.E.Gunson, Spatial patterns and factors influencing small vertebrate fauna road-kill aggregations, Biol. Conserv. 109 (2003), pp. 15–26.
6. P.Congdon, Applied Bayesian Hierarchical Methods, Chapman & Hall/CRC, Boca Raton, 2010.
7. M.K.Cowles and B.P.Carlin, Markov Chain Monte Carlo convergence diagnostics:A comparative review, J. Amer. Statist. Assoc. 91 (1996), pp. 883–904. Available at http://www.scopus.com/inward/record.url?eid=2-s2.0-0030539336&partnerID=40&md5=03fcaf49c53997932bd34dddf8163e72.
8. S.M.Easa and Y.Hassan, Development of transitioned vertical curve Iproperties. Transp. Res. A-Pol. 34 (2000), pp. 481–496. doi:10.1016/s0965-8564(99)00036-1.
9. K.El-Basyouny and T.Sayed, Collision prediction models using multivariate Poisson-lognormal regression, Accid. Anal. Prev. 41 (2009), pp. 820–828.
10. R.J.Fensham and R.J.Fairfax, Water-remoteness for grazing relief in Australian arid-lands, Biol. Conserv. 141 (2008), pp. 1447–1460. doi:10.1016/j.biocon.2008.03.016.
11. A.Gelman, J.B.Carlin, H.S.Stern, D.B.Dunson, A.Vehtari, and D.B.Rubin, Bayesian Data Analysis, CRC Press, Boca Raton, 2013.
12. A.Gelman, J.B.Carlin, H.S.Stern, & D.B.Rubin, Bayesian Data Analysis:Texts in Statistical Science, Chapman & Hall, London, 2004.
13. A.Gelman, A.V.D.David, Z.Huang, and W.B.John, Using redundant parameterizations to fit hierarchical models. J. Comput. Graph. Statist. 17 (2008), pp. 95–122.
14. M.Ghosh, K.Natarajan, L.A.Waller, and D.Kim, Hierarchical Bayes GLMs for the analysis of spatial data:An application to disease mapping, J. Statist. Plann. Inference, 75 (1999), pp. 305–318. doi:10.1016/s0378-3758(98)00150-5.
15. M.Graf, Spatial discrete hazards using Hierarchical Bayesian Modeling. The Institute of Structural Engineering Group Risk and Safety PhD Seminar on Bayesian Networks and Bayesian Hierarchical Analysis in Engineering, Zurich, Switzerland, 2009.
16. K.E.Gunson, G.Mountrakis, and L.J.Quackenbush, Spatial wildlife-vehicle collision models:A review of current work and its application to transportation mitigation projects, J. Environ. Manage. 92 (2011), pp. 1074–1082. doi:10.1016/j.jenvman.2010.11.027.
17. M.M.Haque, H.C.Chin, and H.Huang, Modeling fault among motorcyclists involved in crashes, Accident Anal. Prev. 41 (2009), pp. 327–335.
18. J.H.Hedlund, P.D.Curtis, G.Curtis, and A.F.Williams, Methods to reduce traffic crashes involving deer:What works and what does not, Traffic Inj. Prev. 5 (2004), pp. 122–131. doi:10.1080/15389580490435079.
19. H.Huang and M.Abdel-Aty, Multilevel data and Bayesian analysis in traffic safety, Accident Anal. Prev. 42 (2010), pp. 1556–1565. doi:10.1016/j.aap.2010.03.013.
20. P.P.Jovanis and H.-L.Chang, Modeling the relationship of accidents to miles traveled, Transp. Res. Rec.1068 (1986), pp. 42–51. Available at http://www.scopus.com/inward/record.url?eid=2-s2.0-0022882374&partnerID=40&md5=f8e156fa25b0f4e71b86d89c8b266d90
21. T.L.Joyce and S.P.Mahoney, Spatial and temporal distributions of moose--vehicle collisions in Newfoundland, Wildlife Soc. Bull. 29 (2001), pp. 281–291.
22. R.L.Langley & J.Mathison, Worldwide Characteristics and Mitigation Strategies for Motor Vehicle–Animal Collisions. Traffic Accidents:Causes and Outcomes. Nova Science Publishers, New York, 2008, pp. 75–96.
23. Y.Lao, Y.-J.Wu, J.Corey, and Y.Wang, Modeling animal–vehicle collisions using diagonal inflated bivariate Poisson regression, Accident Anal. Prev. 43 (2011), pp. 220–227. doi:10.1016/j.aap.2010.08.013.
24. J.Law, R.Haining, R.Maheswaran, and T.Pearson, Analyzing the relationship between smoking and coronary heart disease at the small area level:ABayesian approach to spatial modeling, Geogr. Anal. 38 (2006), pp. 140–159.
25. J.Ma, K.M.Kockelman, and P.Damien, A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods, Accid. Anal. Prev. 40 (2008), pp. 964–975. doi:10.1016/j.aap.2007.11.002.
26. Y.C.MacNab, Bayesian spatial and ecological models for small-area accident and injury analysis, Accid. Anal. Prev. 36 (2004), pp. 1019–1028. doi:10.1016/j.aap.2002.05.001.
27. M.A.Maes, M.R.Dann, and A.K.Midtgaard, Spatial hazard rate modeling using hierarchicalBayes methods. Aust. J. Struct. Eng. 9 (2009), pp. 45–54.
28. M.Maes, M.Dann, S.Sarkar, and A.Midtgaard, Event occurrences within a spatial network using hierarchical Bayes, International Forum on Engineering Decision Making, Vol. 10, 2007.
29. J.E.Malo, F.Suárez, and A.Díez, Can we mitigate animal–vehicle accidents using predictive models?, J. Appl. Ecol. 41 (2004), pp. 701–710. doi:10.1111/j.0021-8901.2004.00929.x.
30. S.-P.Miaou and H.Lum, Modeling vehicle accidents and highway geometric design relationships, Accid. Anal. Prev. 25 (1993), pp. 689–709. doi:10.1016/0001-4575(93)90034-t
31. S.-P.Miaou, J.J.Song, and B.K.Mallick, Roadway traffic crash mapping:A space-time modeling approach, J. Trans. Stat. 6 (2003), pp. 33–58.
32. S.Mitra and S.Washington, On the nature of over-dispersion in motor vehicle crash prediction models, Accid. Anal. Prev. 39 (2007), pp. 459–468. doi:10.1016/j.aap.2006.08.002.
33. C.Plug, J.Xia, and C.Caulfield, Spatial and temporal visualisation techniques for crash analysis, Accid. Anal. Prev. 43 (2011), pp. 1937–1946. Available at http://www.sciencedirect.com/science/article/pii/S0001457511001266.
34. M.J.Puglisi, J.S.Lindzey, and E.D.Bellis, Factors associated with highway mortality of white-tailed deer, J. Wildl. Manage. 38 (1974), pp. 799–807.
35. M.A.Quddus, Modelling area-wide count outcomes with spatial correlation and heterogeneity:An analysis of London crash data, Accid. Anal. Prev. 40 (2008), pp. 1486–1497. Available at http://www.scopus.com/inward/record.url?eid=2-s2.0-46149122279&partnerID=40&md5=bf07f636f27753174a0738ed1ed424e0.
36. D.Ramp, J.Caldwell, K.A.Edwards, D.Warton, and D.B.Croft, Modelling of wildlife fatality hotspots along the snowy mountain highway in New South Wales, Australia, Biol. Conserv. 126 (2005), pp. 474–490.
37. P.Rowden, D.Steinhardt, and M.Sheehan, Road crashes involving animals in Australia, Accid. Anal. Prev. 40 (2008), pp. 1865–1871. doi:10.1016/j.aap.2008.08.002.
38. G.G.Schultz, D.J.Thurgood, A.N.Olsen, and C.S. Reese, Analyzing raised median safety impacts using Bayesian methods, Transport Res. Rec.:J. Transport. Res. Board 2223 (2011), pp. 96–103.
39. A.Seiler, Predicting locations of moose–vehicle collisions in Sweden, J. Appl. Ecol. 42 (2005), pp. 371–382. doi:10.1111/j.1365-2664.2005.01013.x.
40. I.Thomas, Spatial data aggregation:Exploratory analysis of road accidents, Accid. Anal. Prev. 28 (1996), pp. 251–264. doi:10.1016/0001-4575(95)00067-4.
41. S.P.Miaou, The relationship between truck accidents and geometric design of road sections:Poisson versus negative binomial regressions, Accid. Anal. Prev. 26 (1994), pp. 471–482.
42. D.Lord, S.P.Washington, and J.N.Ivan, Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes:Balancing statistical fit and theory, Accid. Anal. Prev. 37 (2005), pp. 35–46. doi:10.1016/j.aap.2004.02.004.
43. M.J.Maher, Accident migration - a statistical explanation? Traffic Eng. Control 28 (1987), pp. 480–483.
44. S.Mitra and S.Washington, On the nature of over-dispersion in motor vehicle crash prediction models, Accid. Anal. Prev. 39 (2007), pp. 459–468.
45. S.Bowman, Surface hydrology of the cape-to-cape region of Western Australia, Report no. 21, Department of Water, Western Australia Surface Water Hydrology, 2007.
46. D.Spiegelhalter, A.Thomas, N.Best, and D.Lunn, WinBUGS user manual, version 1.4.1, 2004.
47. G.W.Arnold, D.E.Steven, and J.Weeldenburg, The use of surrounding farmland by western grey kangaroos and their impact on crop production, Aust. Wildl. Res. 16 (1989), pp. 85–93.