Temporal stability of driver injury severities in animal-vehicle collisions: A random parameters with heterogeneity in means (and variances) approach

Analytic Methods in Accident Research

Volumn 26, Issue , 2020, Pages

  Al Bdairi, Nabeel Saleem Saad ^a   Behnood, Ali ^b   Hernandez, Salvador ^c  

^a WASIT UNIVERSITY   (Iraq)

^b PURDUE UNIVERSITY   (United States)

^c Oregon State University   (United States)

Author keywords

Animal vehicle collision; Heterogeneity in means and variance; Random parameters; Unobserved heterogeneity

Indexed keywords

ANIMALS; HIGHWAY ACCIDENTS; ROAD VEHICLES; STABILITY;

DRIVER INJURY SEVERITIES; EXPLANATORY VARIABLES; HETEROGENEITY-IN-MEANS AND VARIANCE; LIKELIHOOD RATIO TESTS; METHODOLOGICAL APPROACH; RANDOM PARAMETERS; UNOBSERVED HETEROGENEITY; VEHICLE COLLISIONS;

PARAMETER ESTIMATION;

EID: 85079894171     PISSN: 22136657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amar.2020.100120     Document Type: Article

References (55)

1. Al-Bdairi, N., Hernandez, S., An empirical analysis of run-off-road injury severity crashes involving large trucks. Accident Analysis and Prevention 102 (2017), 93–100.
2. Al-Bdairi, N., Hernandez, S., Anderson, J., Contributing factors to run-off-road crashes involving large trucks under lighted and dark conditions. Journal of Transportation Engineering, Part A: Systems 144 (2018), 1–9.
3. Alnawmasi, N., Mannering, F., A statistical assessment of temporal instability in the factors determining motorcyclist injury severities. Analytic Methods in Accident Research 100090 (2019), 1–20.
4. Anderson, J., Hernandez, S., Roadway classifications and the accident injury severities of heavy-vehicle drivers. Analytic Methods in Accident Research 15 (2017), 17–28.
5. Behnood, A., Mannering, F., Time-of-day variations and temporal instability of factors affecting injury severities in large-truck crashes. Analytic Methods in Accident Research, 23, 2019, 100102.
6. Behnood, A., Mannering, F., The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes. Traffic Injury Prevention 18 (2017), 456–462.
7. Behnood, A., Mannering, F., Determinants of bicyclist injury severities in bicycle-vehicle crashes: A random parameters approach with heterogeneity in means and variances. Analytic Methods in Accident Research 16 (2017), 35–47.
8. Behnood, A., Mannering, F., The effect of passengers on driver-injury severities in single-vehicle crashes: A random parameters heterogeneity-in-means approach. Analytic Methods in Accident Research 14 (2017), 41–53.
9. Behnood, A., Mannering, F., An empirical assessment of the effects of economic recessions on pedestrian-injury crashes using mixed and latent-class models. Analytic Methods in Accident Research 12 (2016), 1–17.
10. Behnood, A., Mannering, F., The temporal stability of factors affecting driver-injury severities in single-vehicle crashes: Some empirical evidence. Analytic Methods in Accident Research 8 (2015), 7–32.
11. Behnood, A., Roshandeh, A., Mannering, F., Latent class analysis of the effects of age, gender, and alcohol consumption on driver-injury severities. Analytic Methods in Accident Research 3–4 (2014), 56–91.
12. Boggs, A., Wali, B., Khattak, A., Exploratory analysis of automated vehicle crashes in California: A text analytics & hierarchical Bayesian heterogeneity-based approach. Accident Analysis and Prevention, 135, 2020, 105354.
13. Cerwick, D., Gkritza, K., Shaheed, M., Hans, Z., A comparison of the mixed logit and latent class methods for crash severity analysis. Analytic Methods in Accident Research 3–4 (2014), 11–27.
14. Diaz-varela, E., Vazquez-gonzalez, I., Marey-pérez, M., Álvarez-lópez, C., Assessing methods of mitigating wildlife – vehicle collisions by accident characterization and spatial analysis. Transportation Research Part D 16 (2011), 281–287.
15. Eker, U., Ahmed, S., Fountas, G., Anastasopoulos, P., An exploratory investigation of public perceptions towards safety and security from the future use of flying cars in the United States. Analytic Methods in Accident Research, 23, 2019, 100103.
16. Found, R., Boyce, M., Predicting deer-vehicle collisions in an urban area. Journal of Environmental Management 92 (2011), 2486–2493.
17. Fountas, G., Anastasopoulos, P., Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances. Analytic Methods in Accident Research 20 (2018), 30–45.
18. Fountas, G., Anastasopoulos, P., A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities. Analytic Methods in Accident Research 15 (2017), 1–16.
19. Fountas, G., Anastasopoulos, P., Abdel-Aty, M., Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates. Analytic Methods in Accident Research 18 (2018), 57–68.
20. Fountas, G., Anastasopoulos, P., Mannering, F., Analysis of vehicle accident-injury severities: A comparison of segment- versus accident-based latent class ordered probit models with class-probability functions. Analytic Methods in Accident Research 18 (2018), 15–32.
21. Fountas, G., Pantangi, S., Hulme, K., Anastasopoulos, P., The effects of driver fatigue, gender, and distracted driving on perceived and observed aggressive driving behavior: a correlated grouped random parameters bivariate probit approach. Analytic Methods in Accident Research, 22, 2019, 100091.
22. Gong, L., Fan, W. (David), Modeling single-vehicle run-off-road crash severity in rural areas: accounting for unobserved heterogeneity and age difference. Accident Analysis and Prevention 101 (2017), 124–134.
23. Hedlund, J., Curtis, P., Curtis, G., Williams, A., Methods to reduce traffic crashes involving deer: what works and what does not. Traffic Injury Prevention 5 (2004), 122–131.
24. Heydari, S., Fu, L., Thakali, L., Joseph, L., Benchmarking regions using a heteroskedastic grouped random parameters model with heterogeneity in mean and variance: applications to grade crossing safety analysis. Analytic Methods in Accident Research 19 (2018), 33–48.
25. Hothorn, T., Müller, J., Held, L., Möst, L., Mysterud, A., Temporal patterns of deer-vehicle collisions consistent with deer activity pattern and density increase but not general accident risk. Accident Analysis and Prevention 81 (2015), 143–152.
26. Huang, H., Chang, F., Zhou, H., Lee, J., Modeling unobserved heterogeneity for zonal crash frequencies: a Bayesian multivariate random-parameters model with mixture components for spatially correlated data. Analytic Methods in Accident Research, 24, 2019, 100105.
27. Huijser, M., Duffield, J., Clevenger, A., Ament, R., McGowen, P., Cost-benefit analyses of mitigation measures aimed at reducing collisions with large ungulates in the United States and Canada: a decision support tool. Ecology and Society, 2009, 14.
28. Kim, J.-K., Ulfarsson, G., Kim, S., Shankar, V., Driver-injury severity in single-vehicle crashes in California: a mixed logit analysis of heterogeneity due to age and gender. Accident Analysis and Prevention 50 (2013), 1073–1081.
29. Knapp, K., Yi, X., Oakasa, T., Deer-vehicle crash countermeasures effectiveness research review. Proceedings of the 2003 Mid-Continent Transportation Research Symposium, 2003, Iowa State University, Ames, Iowa.
30. Kockelman, K., Kweon, Y.-J., Driver injury severity: an application of ordered probit models. Accident Analysis and Prevention 34 (2002), 313–321.
31. Lao, Y., Wu, Y., Corey, J., Wang, Y., Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression. Accident Analysis and Prevention 43 (2011), 220–227.
32. Lao, Y., Zhang, G., Wu, Y., Wang, Y., Modeling animal – vehicle collisions considering animal – vehicle interactions. Accident Analysis and Prevention 43 (2011), 1991–1998.
33. Liu, P., Fan, W., Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: a case study of North Carolina. Accident Analysis and Prevention, 135, 2020, 105388.
34. Mannering, F., Temporal instability and the analysis of highway accident data. Analytic Methods in Accident Research 17 (2018), 1–13.
35. Mannering, F., Shankar, V., Bhat, C., Unobserved heterogeneity and the statistical analysis of highway accident data. Analytic Methods in Accident Research 11 (2016), 1–16.
36. Marcoux, A., Riley, S., Driver knowledge, beliefs, and attitudes about deer – vehicle collisions in southern Michigan. Human-Wildlife Interactions 4 (2010), 47–55.
37. Marcoux, R., Yasmin, S., Eluru, N., Rahman, M., Evaluating temporal variability of exogenous variable impacts over 25 years: An application of scaled generalized ordered logit model for driver injury severity. Analytic Methods in Accident Research 20 (2018), 15–29.
38. Mcfadden, D., Train, K., Mixed MNL Models for Discrete Response. Journal of Applied Econometrics 15 (2000), 447–470.
39. Milton, J., Shankar, V., Mannering, F., Highway accident severities and the mixed logit model: an exploratory empirical analysis. Accident Analysis and Prevention 40 (2008), 260–266.
40. Moore, D., Schneider, W., Savolainen, P., Farzaneh, M., Mixed logit analysis of bicyclist injury severity resulting from motor vehicle crashes at intersection and non-intersection locations. Accident Analysis and Prevention 43 (2011), 621–630.
41. National Insurance Crime Bureau (NICB), 2018. Animal-Related Insurance Claims Top 1.7 Million in Four Years. January 27, 2020. < https://www.nicb.org/news/news-releases/animal-related-insurance-claims-top-17-million-four-years>.
42. NHTSA, Traffic Safety Facts 2015: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System. 2015, U.S. Department of Transportation, Washington, D.C.
43. Savolainen, P., Ghosh, I., Examination of factors affecting driver injury severity in Michigan's single-vehicle – deer crashes. Transportation Research Record: Journal of the Transportation Research Board, 2008, 17–25.
44. Seraneeprakarn, P., Huang, S., Shankar, V., Mannering, F., Venkataraman, N., Milton, J., Occupant injury severities in hybrid-vehicle involved crashes: a random parameters approach with heterogeneity in means and variances. Analytic Methods in Accident Research 15 (2017), 41–55.
45. Shaheed, M., Gkritza, K., A latent class analysis of single-vehicle motorcycle crash severity outcomes. Analytic Methods in Accident Research 2 (2014), 30–38.
46. Shaheed, M., Gkritza, K., Carriquiry, A., Hallmark, S., Analysis of occupant injury severity in winter weather crashes: a fully Bayesian multivariate approach. Analytic Methods in Accident Research 11 (2016), 33–47.
47. Sullivan, T., Williams, A., Messmer, T., Hellinga, L., Kyrychenko, S., Effectiveness of temporary warning signs in reducing deer – vehicle collisions during mule deer migrations. Wildlife Society Bulletin 32 (2004), 907–915.
48. U.S. Department of Transportation/Federal Highway Administration, 2016. 2015 Status of the Nation's Highways, Bridges, and Transit: Conditions and Performance. Washington DC.
49. Vanlaar, W., Barrett, H., Hing, M., Brown, S., Robertson, R., Canadian wildlife-vehicle collisions: an examination of knowledge and behavior for collision prevention. Journal of Safety Research 68 (2019), 181–186.
50. Venkataraman, N., Shankar, V., Ulfarsson, G., Deptuch, D., A heterogeneity-in-means count model for evaluating the effects of interchange type on heterogeneous influences of interstate geometrics on crash frequencies. Analytic Methods in Accident Research 2 (2014), 12–20.
51. Washington, S., Karlaftis, M., Mannering, F., Statistical and Econometric Methods for Transportation Data Analysis. 2nd ed., 2011, Chapman & Hall/CRC, Boca Raton, FL.
52. Wilkins, D., Kockelman, K., Jiang, N., Animal-vehicle collisions in Texas: how to protect travelers and animals on roadways. Accident Analysis and Prevention 131 (2019), 157–170.
53. Xiong, Y., Mannering, F., The heterogeneous effects of guardian supervision on adolescent driver-injury severities: a finite-mixture random-parameters approach. Transportation Research Part B 49 (2013), 39–54.
54. Yang, X., Zou, Y., Wu, L., Zhong, X., Wang, Y., Ijaz, M., Peng, Y., Comparative analysis of the reported animal-vehicle collisions data and carcass removal data for hotspot identification. Journal of Advanced Transportation 2019 (2019), 1–13.
55. Yasmin, S., Eluru, N., Bhat, C., Tay, R., A latent segmentation based generalized ordered logit model to examine factors influencing driver injury severity. Analytic Methods in Accident Research 1 (2014), 23–38.