Multivariate Poisson Lognormal Modeling of Weather-Related Crashes on Freeways

Transportation Research Record

Volumn 2672, Issue 38, 2018, Pages 184-198

  Wang, Kai ^a   Zhao, Shanshan ^a   Jackson, Eric ^a  

^a University of Connecticut   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CODES (SYMBOLS); FORECASTING; HIGHWAY ACCIDENTS; METEOROLOGY;

ADVERSE WEATHER; CONDITION; CRASH PREDICTION; CRASH SEVERITY; CRASH TYPE; LOG-NORMAL MODEL; MODEL PREDICTION; MOTOR VEHICLE CRASHES; PREDICTION MODELLING; UNIVARIATE;

COST EFFECTIVENESS;

EID: 85047382797     PISSN: 03611981     EISSN: 21694052     Source Type: Journal    
DOI: 10.1177/0361198118776523     Document Type: Article

References (68)

1. NHTSA. National Highway Traffic Safety Administration. http://www.nhtsa.gov/NCSA
2. Transport Canada, 2011. Road Safety in Canada. http://www.tc.gc.ca/eng/roadsafety/tp-tp15145-1201.htm
3. Brodsky H., Hakkert A., Risk of a Road Accident in Rainy Weather. Accident Analysis and Prevention, Vol. 20, 1988, pp. 161–176.
4. Edward J., The Relationship Between Road Accident Severity and Recorded Weather. Journal of Safety Research, Vol. 29, No. 4, 1998, pp. 249–262.
5. Naik B., Tung L., Zhao S., Khattak A., Weather Impacts on Single-Vehicle Truck Crash Injury Severity. Journal of Safety Research, Vol. 58, 2016, pp. 57–65.
6. Khan G., Qin X., Noyce D., Spatial Analysis of Weather Crash Patterns. Journal of Transportation Engineering, Vol. 134, No. 5, 2008, pp. 191–202.
7. Khattak A., Kantor P., Council F., Role of Adverse Weather in Key Crash Types on Limited-Access Roadways. Implications for Advanced Weather Systems. Transportation Research Record: Journal of the Transportation Research Board, 1998. 1621: 10–19.
8. Amin M., Zareie A., Amador-Jimenez L., Climate Change Modeling and the Weather-related Road Accidents in Canada. Transportation Research Part D, Vol. 32, 2014, pp. 171–183.
9. Eisengerg D., The Mixed Effects of Precipitation on Traffic Crashes. Accident Analysis and Prevention, Vol. 36, 2004, pp. 637–647.
10. Abdel-Aty M., Ekram A., Huang H., Choi K., A Study on Crashes Related to Visibility Obstruction Due to Fog and Smoke. Accident Analysis and Prevention, Vol. 43, No. 5, 2011, pp. 1730–1737.
11. Chen S., Cai C., Wolshon B., From Normal Operation to Evacuation: Single-Vehicle Safety Under Adverse Weather, Topographic, and Operational Conditions. Technical Papers. Natural Hazards Review, Vol. 10, No. 2, 2009, pp. 68–76.
12. Qiu L, Nixon W., Effects of Adverse Weather on Traffic Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2008. 2055: 139–146.
13. Andrey J., Mills B., Leahy M., Suggett J., Weather as a Chronic Hazard for Road Transportation in Canadian Cities. Natural Hazards, Vol. 28, No. 2–3, 2003, pp. 319–343.
14. Brijs T., Karlis D., Wets G., Studying the Effect of Weather Conditions on Daily Crash Counts Using a Discrete Time-Series Model. Accident Analysis & Prevention, Vol. 40, No. 3, 2008, pp. 1180–1190.
15. Ahmed M., Abdel-Aty M., Yu R., Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data. Transportation Research Record: Journal of the Transportation Research Board, 2012. 2280: 51–59.
16. El-Basyouny K., Barua S., Islam M. T., Investigation of Time and Weather Effects on Crash Types Using Full Bayesian Multivariate Poisson Lognormal Models. Accident Analysis & Prevention, Vol. 73, No. 26, 2014, pp. 91–99.
17. Qin X., Noyce D., Lee C., Kinar J., Snowstorm Event-based Crash Analysis. Transportation Research Record: Journal of the Transportation Research Board, 2006. 1948: 135–141.
18. Khattak A., Knapp K., Interstate Highway Crash Injuries During Winter Snow and Non-Snow Events. Transportation Research Record: Journal of the Transportation Research Board, 2001. 1746: 30–36.
19. Young R., Liesman J., Estimating the Relationship Between Measured Wind Speed and Overturning Truck Crashes Using a Binary Logit Model. Accident Analysis and Prevention, Vol. 39, No. 3, 2007, pp. 574–580.
20. Eisenberg D., Warner K., Effects of Snowfalls on Motor Vehicle Collisions, Injuries and Fatalities. American Journal of Public Health, Vol. 95, 2005, pp. 120–124.
21. Andersson A., Chapman L., The Impact of Climate Change on Winter Road Maintenance and Traffic Accidents in West Midlands, UK. Accident Analysis and Prevention, Vol. 43, No. 1, 2011, pp. 284–289.
22. Oh S., Chung K., Chan C., Analysis of Wet Weather Related Collision Concentration Locations: Empirical Assessment of Continuous Risk Profile. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
23. Wu Y., Abdel-Aty M., Lee J., Crash Risk Analysis During Fog Conditions Using Real-Time Traffic Data. Accident Analysis & Prevention, Vol. 114, 2017, pp. 4–11.
24. Ahmed M. M., Abdel-Aty M., Lee J., Yu R., Real-Time Assessment of Fog-Related Crashes Using Airport Weather Data: A Feasibility Analysis. Accident Analysis & Prevention, Vol. 72, 2014, pp. 309–317.
25. Wu Y., Abdel-Aty M., Cai Q., Lee J., Park J., Rear-End Crash Risk Algorithm under Fog Condition Based on Kinematics Analysis. Presented at 96th Annual Meeting of the Transportation Research Board, Washington, D.C., 2017.
26. Mulinazzi T., Schrock S., Mitigating Wind Induced Truck Crashes. Report # MATC-KU: 263, Mid-America Transportation Center, 2010.
27. Hermans E., Brijs T., Stiers T., Offermans C., The Impact of Weather Conditions on Road Safety Investigated on an Hourly Basis. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
28. Baker C.J., Reynolds S., Wind-Induced Accidents of Road Vehicles. Accident Analysis & Prevention, Vol. 24, No. 6, 1992, pp. 559–575.
29. Wanvik P., Effects of Road Lighting: An Analysis Based on Dutch Accident Statistics 1987–2006. Accident Analysis and Prevention, Vol. 41, No. 1, 2009, pp. 123–128.
30. Lord D., Mannering F., The Statistical Analysis of Crash-Frequency Data: A Review and Assessment of Methodological Alternatives. Transportation Research Part A, Vol. 44, No. 5. 2010, pp. 291–305.
31. Mannering F., Bhat C., Analytic Methods in Accident Research: Methodological Frontier and Future Directions. Analytic Methods in Accident Research, Vol. 1. 2014. pp. 1–22.
32. Koetse M., Rietveld P., The Impact of Climate Change and Weather on Transport: An Overview of Empirical Findings. Transportation Research Part D, Vol. 14, No. 3. 2009, pp. 205–221.
33. Theofilatos A., Yannis G., A Review of the Effect of Traffic and Weather Characteristics on Road Safety. Accident Analysis & Prevention, Vol. 72, 2014, pp. 244–256.
34. Ye X., Pendyala R., Washington S., Konduri K., Oh J., A Simultaneous Equations Model of Crash Frequency by Collision Type for Rural Intersections. Safety Science, Vol. 47, No. 3, 2009, pp. 443–452.
35. Ye X., Pendyala R., Shankar V., Konduri K., A Simultaneous Equations Model of Crash Frequency by Severity Level for Freeway Sections. Accident Analysis and Prevention. Vol. 57, 2013, pp. 140–149.
36. Wang C., Quddus M. A., Ison S. G., Predicting Accident Frequency at Their Severity Levels and Its Application in Site Ranking Using a Two-Stage Mixed Multivariate Model. Accident Analysis and Prevention, Vol. 43, 2011, pp. 1979–1990.
37. Chiou Y., Fu C., Modeling Crash Frequency and Severity Using Multinomial Generalized Poisson Model with Error Components. Accident Analysis and Prevention. Vol. 50, 2013, pp. 73–82.
38. Chiou Y., Fu C., Chih-Wei H., Incorporating Spatial Dependence in Simultaneously Modeling Crash Frequency and Severity. Analytic Methods in Accident Research. Vol. 2, 2014, pp. 1–11.
39. Chiou Y., Fu C., Modeling Crash Frequency and Severity with Spatiotemporal Dependence. Analytic Methods in Accident Research. Vol. 5–6, 2015, pp. 43–58.
40. Cai Q., Abdel-Aty M., Lee J., Macro-level Vulnerable Road Users Crash Analysis: A Bayesian Joint Modeling Approach of Frequency and Proportion. Accident Analysis & Prevention, Vol. 107, 2017, pp. 11–19.
41. Pei X., Wong S., Sze N., A Joint-probability Approach to Crash Prediction Models. Accident Analysis and Prevention, Vol. 43, No. 3, 2011, pp. 1160–1166.
42. Zeng Q., Huang H., Pei X., Wong S., Modeling Nonlinear Relationship Between Crash Frequency by Severity and Contributing Factors by Neural Networks. Analytic Methods in Accident Research. Vol. 10, 2016, pp. 12–25.
43. WinBUGS. MRC Biostatistics Unit. University of Cambridge. https://appdb.winehq.org/objectManager.php?sClass=version&iId=17849&iTestingId=44665
44. Ma J., Kockelman K., Bayesian Multivariate Poisson-Lognormal Regression for Models of Injury Count by Severity. Transportation Research Record: Journal of the Transportation Research Board, 2006. 1950: 24–34.
45. Ma J., Kockelman K., Damien P., A Multivariate Poisson-Lognormal Regression Model for Prediction of Crash Counts by Severity, Using Bayesian Methods. Accident Analysis and Prevention. Vol. 40, No. 3. 2008, pp. 964–975.
46. Park E. S., Lord D., Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity. Transportation Research Record: Journal of the Transportation Research Board, 2007. 2019: 1–6.
47. Lee J., Abdel-Aty M., Jiang X., Multivariate Crash Modeling for Motor Vehicle and Non-motorized Models at the Macroscopic Level. Accident Analysis and Prevention, Vol. 78, 2015, pp. 146–154.
48. Chib S., Winkelmann R., Markov Chain Monte Carlo Analysis of Correlated Count Data. Journal of Business and Economic Statistics, Vol. 19, No. 4, 2001, pp. 428–435.
49. Aguero-Valverde J., Jovanis P. P., Bayesian Multivariate Poisson Log-normal Models for Crash Severity Modeling and Site Ranking. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
50. El-Basyouny K., Sayed T., Collision Prediction Models Using Multivariate Poisson-Lognormal Regression. Accident Analysis and Prevention, Vol. 41, No. 4, 2009, pp. 820–828.
51. Zhao M., Liu C., Li W., Sharma A., Multivariate Poisson-Lognormal Model for Analysis of Crashes on Urban Signalized Intersections Approach. Journal of Transportation Safety & Security, Vol. 10, No. 3, 2018, pp. 251–265.
52. Anastasopoulos P., Shankar V., Haddock J., Mannering F., A Multivariate Tobit Analysis of Highway Accident-Injury-Severity Rates. Accident Analysis and Prevention, Vol. 45, 2012, pp. 110–119.
53. Dong C., Clarke D., Yan X., Khattak A., Huang B., Multivariate Random-Parameter Zero-Inflated Negative Binomial Regression Model: An Application to Estimate Crash Frequencies at Intersections. Accident Analysis and Prevention, Vol. 70, 2014, pp. 320–329.
54. Barua S., El-Basyouny K., Islam M., A Full Bayesian Multivariate Count Data Model of Collision Severity with Spatial Correlation. Analytic Methods in Accident Research, Vol. 3–4. 2014, pp. 28–43.
55. Wang Y., Kockelman K., A Poisson-Lognormal Conditional-Autoregressive Model for Multivariate Spatial Analysis of Pedestrian Crash Counts Across Neighborhoods. Accident Analysis and Prevention, Vol. 60, 2013, pp. 71–81.
56. Barua S., El-Basyouny K., Islam M., Multivariate Random Parameters Collision Count Data Models with Spatial Heterogeneity. Analytic Methods in Accident Research, Vol. 9, 2016, pp. 1–15.
57. Rue H., Martino S., Approximate Bayesian Inference for Hierarchical Gaussian Markov Random Field Models. Journal of Statistical Planning and Inference, Vol. 137, No. 10., 2007, pp. 3177–3192.
58. Serhiyenko V., Mamun S., Ivan J., Ravishanker N., Fast Bayesian Inference for Modeling Multivariate Crash Counts. Analytic Methods in Accident Research, Vol. 10, 2016, pp. 44–53.
59. Wang K., Ivan J., Ravishanker N., Jackson E., Multivariate Poisson Lognormal Modeling of Crashes by Type and Severity on Rural Two Lane Highways. Accident Analysis and Prevention, Vol. 99, 2017, pp. 6–19.
60. Aitchison J., Ho C.H., The Multivariate Poisson Lognormal Distribution. Biometrika. Vol. 76, No. 4, 1989, pp. 643–653.
61. Chib S., Winkelmann R., Markov Chain Monte Carlo Analysis of Correlated Count Data. Journal of Business and Economic Statistics, Vol. 19, No. 4, 2001, pp. 428–435.
62. Connecticut Department of Transportation. http://www.ct.gov/dot/site/default.asp
63. National Center for Environmental Information. National Oceanic and Atmospheric Administration. Asheville, NC. https://www.ncdc.noaa.gov/cdo-web/datatools/lcd
64. Connecticut Crash Data Repository. University of Connecticut. http://www.ctcrash.uconn.edu/
65. Model Minimum Uniform Crash Criteria (MMUCC). Governors Highway Safety Association, National Highway Traffic Safety Administration. https://www.transportation.gov/government/traffic-records/model-minimum-uniform-crash-criteria-mmucc-0
66. Roy U., Dissanayake S., Comparison of Factors Associated with Run-off-road and Non-run-off-road Crashes in Kansas. Journal of Transportation Research Forum, Vol. 50, No. 2, 2011, pp. 69–86.
67. Liu C., Ye T., Run-off-road Crashes: An On-scene Perspective. National Highway Traffic Safety Administration. Final Report of National Center for Statistics and Analysis. Report No. DOT HS 811 50. 2011. US Department of Transportation.
68. Wang K., Ivan J., Burnicki A., Mamun S., Predicting Local Road Crashes Using Socioeconomic and Land Cover Data. Journal of Transportation Safety & Security. Vol. 9, No. 3, 2017, pp. 301–318.