Development of planning level transportation safety tools using Geographically Weighted Poisson Regression

Accident Analysis and Prevention

Volumn 42, Issue 2, 2010, Pages 676-688

  Hadayeghi, Alireza ^a   Shalaby, Amer S ^b   Persaud, Bhagwant N ^c  

^a CIMA+   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

^c RYERSON UNIVERSITY   (Canada)

Author keywords

Generalized Linear Models; Geographically Weighted Poisson Regression; Local regression models; Model calibration; Safety planning models; Spatial relationships

Indexed keywords

GENERALIZED LINEAR MODEL; LOCAL REGRESSION MODELS; MODEL CALIBRATION; POISSON REGRESSION; SAFETY PLANNING; SPATIAL RELATIONSHIPS;

CALIBRATION; LAND USE; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD; POISSON EQUATION; REGRESSION ANALYSIS;

POISSON DISTRIBUTION;

ARTICLE; ENVIRONMENTAL PLANNING; GEOGRAPHIC INFORMATION SYSTEM; HUMAN; METHODOLOGY; POISSON DISTRIBUTION; SAFETY; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; ENVIRONMENT DESIGN; GEOGRAPHIC INFORMATION SYSTEMS; HUMANS; MODELS, STATISTICAL; POISSON DISTRIBUTION; SAFETY MANAGEMENT;

EID: 76049106306     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2009.10.016     Document Type: Article

References (30)

1. Aguero-Valverde J., and Jovanis P.P. Spatial analysis of fatal and injury crashes in Pennsylvania. Accident Analysis and Prevention 38 3 (2006) 618-625
2. Cameron A.C., and Trivedi P.K. Regression Analysis of Count Data (1998), Cambridge University Press
3. Congdon P. Modelling spatially varying impacts of socioeconomic predictors on mortality outcomes. Journal of Geographical Systems 5 2 (2003) 161-184
4. de Guevara F.L., Washington S.P., and Oh J. Forecasting crashes at the planning level: simultaneous negative binomial crash model applied in Tucson, Arizona. Transportation Research Record 1897 (2004) 191-199
5. Du H., and Mulley C. The relationship between transport accessibility and land value: a local model approach with geographically weighted regression. Proceedings of the 85th Annual Meeting of the Transportation Research Board (2006), National Research Council, Washington, DC
6. EMME/2 User's Guide Manual Release 9. 1998 INRO Consultants INC.
7. Fotheringham A.S., Brunsdon C., and Charlton M. Geographically Weighted Regression the analysis of spatially varying relationships (2002), John Wiley & Sons, Ltd.
8. Guo L., Ma Z., and Zhang L. Comparison of bandwidth selection in application of geographically weighted regression: a case study. Canadian Journal of Forest Research 38 9 (2008) 2526-2534
9. Hadayeghi A., Shalaby A.S., and Persaud B. Macro-level accident prediction models for evaluating safety of urban transportation systems. Transportation Research Record 1840 (2003) 87-95
10. Hadayeghi A., Shalaby A.S., Persaud B., and Cheung C. Temporal transferability and updating of zonal level accident prediction models. Accident Analysis and Prevention 38 3 (2006) 579-589
11. Hadayeghi A., Shalaby A.S., and Persaud B. Safety prediction models: proactive tool for safety evaluation in urban transportation planning applications. Transportation Research Record 2019 (2007) 225-236
12. Hadayeghi, A., 2009. Use of advanced techniques to estimate zonal level safety planning models and examine their temporal transferability. Ph.D. Thesis. Department of Civil Engineering, University of Toronto.
13. Hauer E. Observational Before-After Studies in Road Safety: Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety (1997), Pergamon, Elservier Science Ltd., Oxford, UK
14. Interactive Highway Safety Design Model (IHSDM). Federal Highway Administration, US Department of Transportation. http://www.tfhrc.gov/safety/ihsdm/ihsdm.htm, accessed in May 2009.
15. LeSage, J.P., 2001. A Family of Geographically Weighted Regression Models. Department of Economics, University of Toledo. http://www.spatial-econometrics.com/html/bgwr.pdf, accessed in May 2009.
16. Levine N., Kim K.E., and Nitz L.H. Spatial analysis of Honolulu motor vehicle crashes: II. Zonal generators. Accident Analysis and Prevention 27 5 (1995) 675-685
17. Levine N. CrimeStat III: A Spatial Statistics Program for the Analysis of Crime Incident Locations (version 3.0) (2004), Ned Levine & Associates/National Institute of Justice, Houston, TX/Washington, DC
18. Lovegrove G.R., and Sayed T. Macro-level collision prediction models for evaluating neighbourhood traffic safety. Proceedings of Presented at 6th Transportation Specialty Conference (2005), Canadian Society of Civil Engineering, Toronto, Ontario
19. Miaou S.P. The relationship between truck accidents and geometric design of road sections: poisson versus negative binomial regressions. Accident Analysis and Prevention 26 4 (1994) 471-482
20. Miaou S.P., Song J.J., and Mallick B.K. Roadway traffic crash mapping: a space-time modeling approach. Journal of Transportation Statistics, Bureau of Transportation Statistics 6 1 (2003) 33-57
21. Nakaya T. Local spatial interaction modelling based on the geographically weighted regression approach. GeoJournal 53 (2001) 347-358
22. Nakaya T., Fotheringham A.S., Brunsdon C., and Charlton M. Geographically weighted poisson regression for disease association mapping. Statistics in Medicine 24 17 (2005) 2695-2717
23. Oh J., Lyon C., Washington S., Persaud B., and Bared J. Validation of FHWA crash models for rural intersection lessons learned. Transportation Research Record 1840 (2003) 41-49
24. Park N., and Zhao F. Estimation of AADT Using geographically weighted regression models. Proceedings of the 83rd Annual Meeting of the Transportation Research Board (2004), National Research Council, Washington DC
25. Silverman B.W. Density Estimation for Statistics and Data Analysis. Statistics and Applied Probability (1986), Chapman and Hall, London
26. Wang W., and Abdel-Aty M. Temporal and spatial analyses of rear-end crashes at signalized intersections. Accident Analysis and Prevention 38 6 (2006) 1137-1150
27. Washington, S., Schalkwyk, I.V., Meyer, M., Dumbaugh, E., Zoll, M., 2006. Incorporating safety into long-range transportation planning. NCHRP Report 546, TRB. National Cooperative Highway Research Program, Washington D.C.
28. Wheeler D., and Calder C. An assessment of coefficient accuracy in linear regression models with spatially varying coefficients. Journal of Geographical Systems. 9 2 (2007) 145-166
29. Wheeler D., and Tiefelsdorf M. Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems. 7 2 (2005) 161-187
30. Zhao, F., Chow, L., Li, M., Liu, X., 2005. A Transit ridership model based on geographically weighted regression and service quality variables. Report DO97591, Lehman Center for Transportation Research, Department of Civil and Environmental Engineering, Florida International University.