Joint modeling of pedestrian and bicycle crashes: Copula-based approach

Transportation Research Record

Volumn 2601, Issue , 2016, Pages 119-127

  Nashad, Tammam ^a   Yasmin, Shamsunnahar ^a   Eluru, Naveen ^a   Lee, Jaeyoung ^a   Abdel Aty, Mohamed A ^a  

^a University of Central Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BICYCLES; ECONOMICS; MOTOR TRANSPORTATION; PEDESTRIAN SAFETY; SPORTING GOODS;

ACTIVE MODE; BICYCLE CRASHES; COUNT MODELS; CRASH FREQUENCY; EXOGENOUS VARIABLES; FREQUENCY ANALYSIS; JOINT MODELS; PEDESTRIAN CRASHES; TRAFFIC ANALYSIS ZONES; TRANSPORTATION SAFETY;

LAND USE;

EID: 85010878283     PISSN: 03611981     EISSN: 21694052     Source Type: Journal    
DOI: 10.3141/2601-14     Document Type: Article

References (40)

1. Traffic Safety Facts 2013: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System. DOT HS 812 139. NHTSA, U.S. Department of Transportation, 2015.
2. Jovanis, P. P., and H. Chang. Modeling the Relationship of Accidents to Miles Traveled. In Transportation Research Record 1068, TRB, National Research Council, Washington, D.C., 1986, pp. 42-51.
3. Miaou, S.-P., and H. Lum. A Statistical Evaluation of the Effects of Highway Geometric Design on Truck Accident Involvements. In Transportation Research Record 1407, TRB, National Research Council, Washington, D.C., 1993, pp. 11-23.
4. Abdel-Aty, M., and E. Radwan. Modeling Traffic Accident Occurrence and Involvement. Accident Analysis and Prevention, Vol. 32, 2000, pp. 633-642.
5. Miaou, S.-P., J. J. Song, and B. K. Mallick. Roadway Traffic Crash Mapping: A Space-Time Modeling Approach. Journal of Transportation and Statistics, Vol. 6, 2003, pp. 33-58.
6. Aguero-Valverde, J., and P. P. Jovanis. Analysis of Road Crash Frequency with Spatial Models. In Transportation Research Record: Journal of the Transportation Research Board, No. 2061, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 55-63.
7. Lord, D., and L. F. Miranda-Moreno. Effects of Low Sample Mean Values and Small Sample Size on the Estimation of the Fixed Dis persion Parameter of Poisson-gamma Models for Modeling Motor Vehicle Crashes: A Bayesian Perspective. Safety Science, Vol. 46, No. 5, 2008, pp. 751-770.
8. Maher, M., and L. Mountain. The Sensitivity of Estimates of Regression to the Mean. Accident Analysis and Prevention, Vol. 41, No. 4, 2009, pp. 861-868.
9. Cheng, L., S. R. Geedipally, and D. Lord. The Poisson-Weibull Generalized Linear Model for Analyzing Motor Vehicle Crash Data. Safety Science, Vol. 54, 2013, pp. 38-42.
10. Peng, Y., D. Lord, and Y. Zou. Applying the Generalized Waring Model for Investigating Sources of Variance in Motor Vehicle Crash Analysis. Accident Analysis and Prevention, Vol. 73, 2014, pp. 20-26.
11. Bhat, C. R., and N. Eluru. A Copula-Based Approach to Accommodate Residential Self-Selection Effects in Travel Behavior Modeling. Transportation Research Part B, Vol. 43, No. 7, 2009, pp. 749-765.
12. Yasmin, S., N. Eluru, A. R. Pinjari and R. Tay. Examining Driver Injury Severity in Two Vehicle Crashes: A Copula Based Approach. Accident Analysis and Prevention, Vol. 66, 2014, pp. 120-135.
13. Wang, K., S. Yasmin, K. C. Konduri, N. Eluru, and J. N. Ivan. A Copula-Based Joint Model of Injury Severity and Vehicle Damage in Two-Vehicle Crashes. Presented at 94th Annual Meeting of the Transportation Research Board, Washington, D.C., 2015.
14. Sener, I. N., N. Eluru, and C. R. Bhat. On Jointly Analyzing the Physical Activity Participation Levels of Individuals in a Family Unit. Journal of Choice Modeling, Vol. 3, No. 3, 2010, pp. 1-38.
15. Ferdous, N., N. Eluru, C. R. Bhat, and I. Meloni. A Multivariate Ordered Response Model System for Adults' Weekday Activity Episode Generation by Activity Purpose and Social Context. Transportation Research Part B, Vol. 44, No. 8-9, 2010, pp. 922-943.
16. Bhat, C. R. The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models. Foundations and Trends in Econometrics, Vol. 7, No. 1, 2014, pp. 1-117.
17. Narayanamoorthy, S., R. Paleti, and C. R. Bhat. On Accommodating Spatial Dependence in Bicycle and Pedestrian Injury Counts by Severity Level. Transportation Research Part B, Vol. 55, 2014, pp. 245-264.
18. Bhat, C. R. The Maximum Approximate Composite Marginal Likelihood (MACML) Estimation of Multinomial Probit-Based Unordered Response Choice Models. Transportation Research Part B, Vol. 45, No. 7, 2011, pp. 923-939.
19. Ma, J., and K. M. Kockelman. Bayesian Multivariate Poisson Regression for Models of Injury Count by Severity. In Transportation Research Record: Journal of the Transportation Research Board, No. 1950, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 24-34.
20. Park, E. S., and D. Lord, Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity. In Transportation Research Record: Journal of the Transportation Research Board, No. 2019, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 1-6.
21. El-Basyouny, K., and T. Sayed. Collision Prediction Models Using Multivariate Poisson-Lognormal Regression. Accident Analysis and Prevention, Vol. 41, No. 4, 2009, pp. 820-828.
22. Lee, J., M. Abdel-Aty, and X. Jiang. Multivariate Crash Modeling for Motor Vehicle and Non-Motorized Modes at the Macroscopic Level. Accident Analysis and Prevention, Vol. 78, 2015, pp. 146-154.
23. Kim, D. G., and S. Washington. The Significance of Endogeneity Problems in Crash Models: An Examination of Left-Turn Lanes in Intersection Crash Models. Accident Analysis and Prevention, Vol. 38, No. 6, 2006, pp. 1094-1100.
24. Ye, X., R. M. Pendyala, S. P. Washington, K. Konduri, and J. Oh. A Simultaneous Equations Model of Crash Frequency by Collision Type for Rural Intersections. Safety Science, Vol. 47, No. 3, 2009, pp. 443-452.
25. Cameron, A. C., T. Li, P. K. Trivedi, and D. M. Zimmer. Modelling the Differences in Counted Outcomes Using Bivariate Copula Models with Application to Mismeasured Counts. Econometrics Journal, Vol. 7, No. 2, 2004, pp. 566-584.
26. Eluru, N., R. Paleti, R. M. Pendyala, and C. R. Bhat. Modeling Multiple Vehicle Occupant Injury Severity: A Copula-Based Multivariate Approach. In Transportation Research Record: Journal of the Transportation Research Board, No. 2165, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 1-11.
27. Rana, T. A., S. Sikder, and A. R. Pinjari. Copula-Based Method for Addressing Endogeneity in Models of Severity of Traffic Crash Injuries: Application to Two-Vehicle Crashes. In Transportation Research Record: Journal of the Transportation Research Board, No. 2147, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 75-87.
28. Trivedi, P. K., and D. M. Zimmer. Copula Modeling: An Introduction for Practitioners. Foundations and Trends in Econometrics. Now Publishers, Inc., Boston, Mass., 2007.
29. Sklar, A. Random Variables, Joint Distribution Functions, and Copulas. Kybernetika, Vol. 9, No. 6, 1973, pp. 449-460.
30. GAUSS. Aptech Systems, Inc., Chandler, Ariz., 2012.
31. Quinn, C. The Health-Economic Applications of Copulas: Methods in Applied Econometric Research. Health Econometrics and Data Group, Department of Economics, University of York, United Kingdom, 2007.
32. Elvik, R. The Non-Linearity of Risk and the Promotion of Environmentally Sustainable Transport. Accident Analysis and Prevention, Vol. 41, No. 4, 2009, pp. 849-855.
33. Cottrill, C. D., and P. V. Thakuriah. Evaluating Pedestrian Crashes in Areas with High Low-Income or Minority Populations. Accident Analysis and Prevention, Vol. 42, No. 6, 2010, pp. 1718-1728.
34. Siddiqui, C., M. Abdel-Aty, and K. Choi. Macroscopic Spatial Analysis of Pedestrian and Bicycle Crashes. Accident Analysis and Prevention, Vol. 45, 2012, pp. 382-391.
35. Wier, M., 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, Vol. 41, No. 1, 2009, pp. 137-145.
36. Wei, F., and G. Lovegrove. An Empirical Tool to Evaluate the Safety of Cyclists: Community Based, Macro-Level Collision Prediction Models Using Negative Binomial Regression. Accident Analysis and Prevention, Vol. 61, 2013, pp. 129-137.
37. Pulugurtha, S. S., and V. Thakur. Evaluating the Effectiveness of On-Street Bicycle Lane and Assessing Risk to Bicyclists in Charlotte, North Carolina. Accident Analysis and Prevention, Vol. 76, 2015, pp. 34-41.
38. Qin, X., and J. N. Ivan. Estimating Pedestrian Exposure Prediction Model in Rural Areas. In Transportation Research Record: Journal of the Transportation Research Board, No. 1773, Transportation Research Board of the National Academies, Washington, D.C., 2001, pp. 89-96.
39. Lee, J., M. Abdel-Aty, and X. Jiang. Development of Zone System for Macro-Level Traffic Safety Analysis. Journal of Transport Geography, Vol. 38, 2014, pp. 13-21.
40. Eluru, N., and C. R. Bhat. A Joint Econometric Analysis of Seat Belt Use and Crash-Related Injury Severity. Accident Analysis and Prevention, Vol. 39, No. 5, 2014, pp. 1037-1049.