Time-of-day variations and temporal instability of factors affecting injury severities in large-truck crashes

Analytic Methods in Accident Research

Volumn 23, Issue , 2019, Pages

  Behnood, Ali ^a   Mannering, Fred ^b  

^a PURDUE UNIVERSITY   (United States)

^b University of South Florida   (United States)

Author keywords

Heterogeneity in means and variances; Large truck; Random parameters logit model; Temporal stability; Transferability; Unobserved heterogeneity

Indexed keywords

DECISION MAKING; PARAMETER ESTIMATION; STABILITY; TRUCK DRIVERS; TRUCK TRANSPORTATION; TRUCKS;

HETEROGENEITY IN MEANS AND VARIANCES; LARGE-TRUCKS; RANDOM PARAMETERS LOGIT; TEMPORAL STABILITY; TRANSFERABILITY; UNOBSERVED HETEROGENEITY;

ACCIDENTS;

EID: 85069005294     PISSN: 22136657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amar.2019.100102     Document Type: Article

References (49)

1. Abay, K., Paleti, R., Bhat, C., The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity. Transportation Research Part B 50 (2013), 74–89.
2. Ahmed, M., Franke, R., Ksaibati, K., Shinstine, D., Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models. Accident Analysis and Prevention 117 (2018), 106–113.
3. Alnawmasi, N., Mannering, F., A statistical assessment of temporal instability in the factors determining motorcyclist injury severities. Analytic Methods in Accident Research 22 (2019), 1–20 100090.
4. Anastasopoulos, P., Mannering, F., An empirical assessment of fixed and random parameter logit models using crash- and non-crash-specific injury data. Accident Analysis and Prevention 43:3 (2011), 1140–1147.
5. Anastasopoulos, P., Sarwar, M., Shankar, V., Safety-oriented pavement performance thresholds: accounting for unobserved heterogeneity in a multi-objective optimization and goal programming approach. Analytic Methods in Accident Research 12 (2016), 35–47.
6. Anderson, J., Hernandez, S., Roadway classifications and the accident injury severities of heavy-vehicle drivers. Analytic Methods in Accident Research 15 (2017), 17–28.
7. 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.
8. 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.
9. Behnood, A., Mannering, F., The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes. Traffic Injury Prevention 18:5 (2017), 456–462.
10. 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.
11. 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.
12. 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.
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. Chang, L.-Y., Mannering, F., Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents. Accident Analysis and Prevention 31:5 (1999), 579–592.
15. Chen, F., Chen, S., Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways. Accident Analysis and Prevention 43:5 (2011), 1677–1688.
16. Fabbri, M., Natale, V., Adan, A., Effect of time of day on arithmetic fact retrieval in a number-matching task. Acta Psychologica 127:2 (2008), 485–490.
17. Fountas, G., Anastasopoulos, P.C., A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities. Analytic Methods in Accident Research 15 (2017), 1–16.
18. Fountas, G., Anastasopoulos, P.C., 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.
19. Fountas, G., Anastasopoulos, P.C., 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.
20. Fountas, G., Anastasopoulos, P.C., 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.
21. Fountas, G., Pantangi, S., Hulme, K., Anastasopoulos, P.C., 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. Hao, W., Kamga, C., Yang, X., Ma, J., Thorson, E., Zhong, M., Wu, C., Driver injury severity study for truck involved accidents at highway-rail grade crossings in the United States. Transportation Research Part F 43 (2016), 379–386.
23. Hasler, B., Forbes, E., Franzen, P., Time-of-day differences and short-term stability of the neural response to monetary reward: a pilot study. Psychiatry Research: Neuroimaging 224:1 (2014), 22–27.
24. Islam, M., Hernandez, S., Large truck-involved crashes: exploratory injury severity analysis. Journal of Transportation Engineering 139:6 (2013), 596–604.
25. Islam, M., Hernandez, S., Modeling injury outcomes of crashes involving heavy vehicles on Texas highways. Transportation Research Record: Journal of the Transportation Research Board 2388 (2013), 28–36.
26. Khorashadi, A., Niemeier, D., Shankar, V., Mannering, F., Differences in rural and urban driver-injury severities in accidents involving large-trucks: an exploratory analysis. Accident Analysis and Prevention 37:5 (2005), 910–921.
27. Lemp, J., Kockelman, K., Unnikrishnan, A., Analysis of large truck crash severity using heteroskedastic ordered probit models. Accident Analysis and Prevention 43:1 (2011), 370–380.
28. Leone, M., Slezak, D., Golombek, D., Sigman, M., Time to decide: diurnal variations on the speed and quality of human decisions. Cognition 158 (2017), 44–55.
29. Malyshkina, N., Mannering, F., Markov switching multinomial logit model: an application to accident-injury severities. Accident Analysis and Prevention 41:4 (2009), 829–838.
30. Mannering, F., Bhat, C., Analytic methods in accident research: methodological frontier and future directions. Analytic Methods in Accident Research 1 (2014), 1–22.
31. 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.
32. McFadden, D., Train, K., Mixed MNL models for discrete response. Journal of Applied Econometrics 15 (2000), 447–470.
33. Morgan, A., Mannering, F., The effects of road-surface conditions, age, and gender on driver-injury severities. Accident Analysis and Prevention 43:5 (2011), 1852–1863.
34. National Highway Traffic Safety Administration, 2018. Traffic safety facts: Large trucks, 2016 Data. Washington, DC.
35. Pahukula, J., Hernandez, S., Unnikrishnan, A., A time of day analysis of crashes involving large trucks in urban areas. Accident Analysis and Prevention 75 (2015), 155–163.
36. Russo, B., Savolainen, P., Schneider, W., Anastasopoulos, P.C., Comparison of factors affecting injury severity in angle collisions by fault status using a random parameters bivariate ordered probit model. Analytic Methods in Accident Research 2 (2014), 21–29.
37. Sarwar, M., Anastasopoulos, P., The effect of long term non-invasive pavement deterioration on accident injury-severity rates: a seemingly unrelated and multivariate equations approach. Analytic Methods in Accident Research 13 (2017), 1–15.
38. Savolainen, P., Mannering, F., Lord, D., Quddus, M., The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. Accident Analysis and Prevention 43:5 (2011), 1666–1676.
39. 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.
40. U.S. Department of Transportation, 2017. Freight Facts and Figures 2017 – Chapter 2: Freight Moved in Domestic and International Trade. Washington, DC.
41. Uddin, M., Huynh, N., Factors influencing injury severity of crashes involving HAZMAT trucks. International Journal of Transportation Science and Technology 7:1 (2018), 1–9.
42. Waseem, M., Ahmed, A., Saeed, T., Factors affecting motorcyclists’ injury severities: an empirical assessment using random parameters logit model with heterogeneity in means and variances. Accident Analysis and Prevention 123 (2019), 12–19.
43. Washington, S., Karlaftis, M., Mannering, F., Statistical and Econometric Methods for Transportation Data Analysis. 2nd ed., 2011, Taylor and Francis, Chapman and Hall/CRC, Boca Raton, FL.
44. 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.
45. Xiong, Y., Tobias, J., Mannering, F., The analysis of vehicle crash injury-severity data: a Markov switching approach with road-segment heterogeneity. Transportation Research Part B 67 (2014), 109–128.
46. 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.
47. Zheng, Z., Lu, P., Lantz, B., Commercial truck crash injury severity analysis using gradient boosting data mining model. Journal of Safety Research 65 (2018), 115–124.
48. Zhu, X., Srinivasan, S., Modeling occupant-level injury severity: an application to large-truck crashes. Accident Analysis and Prevention 43:4 (2011), 1427–1437.
49. Zou, W., Wang, X., Zhang, D., Truck crash severity in New York city: an investigation of the spatial and the time of day effects. Accident Analysis and Prevention 99 (2017), 249–261.