[1. AASHTO, 2010. Highway Safety Manual. American Association of State Highway and Transportation Officials, Washington.]Search in Google Scholar
[2. Abdel-Aty, M., Radwan, A.E., 2000a. Developing crash predictive models for a principal arterial, in: Traffic Safety on Two Continents. pp. 177–194.]Search in Google Scholar
[3. Abdel-Aty, M., Radwan, A.E., 2000b. Modeling traffic accident occurrence and involvement. Accid. Anal. Prev. 32 5, 633–42.10.1016/S0001-4575(99)00094-9]Search in Google Scholar
[4. Abdel-Aty, M., Radwan, A.E., 2000c. Modeling traffic accident occurrence and involvement. Accid. Anal. Prev. 32 5, 633–42.10.1016/S0001-4575(99)00094-9]Search in Google Scholar
[5. Al-ghamdi, A.S., 2002. Using logistic regression to estimate the influence of accident factors on accident severity. Accid. Anal. Prev. 34, 729–741.10.1016/S0001-4575(01)00073-2]Search in Google Scholar
[6. Ambros, J., Sedoník, J., 2016. A Feasibility Study for Developing a Transferable Accident Prediction Model for Czech Regions. Transp. Res. Procedia 14, 2054–2063. doi:10.1016/J.TRPRO.2016.05.10310.1016/J.TRPRO.2016.05.103]Open DOISearch in Google Scholar
[7. Anastasopoulos, P.C., Mannering, F., Shankar, V.N., Haddock, J.E., 2012a. A study of factors affecting highway accident rates using the random-parameters tobit model. Accid. Anal. Prev. 45, 628–33. doi:10.1016/j.aap.2011.09.01510.1016/j.aap.2011.09.015]Open DOISearch in Google Scholar
[8. Anastasopoulos, P.C., Mannering, F., Shankar, V.N., Haddock, J.E., 2012b. A study of factors affecting highway accident rates using the random-parameters tobit model. Accid. Anal. Prev. 45, 628–33. doi:10.1016/j.aap.2011.09.01510.1016/j.aap.2011.09.015]Search in Google Scholar
[9. Anastasopoulos, P.C., Shankar, V.N., Haddock, J.E., Mannering, F., 2012c. A multivariate tobit analysis of highway accident-injury-severity rates. Accid. Anal. Prev. 45, 110–9. doi:10.1016/j.aap.2011.11.00610.1016/j.aap.2011.11.006]Open DOISearch in Google Scholar
[10. Asgarzadeh, M., Verma, S., Mekary, R.A., Courtney, T.K., Christiani, D.C., 2017. The role of intersection and street design on severity of bicycle-motor vehicle crashes. Inj. Prev. 23 3, 179–185. doi:10.1136/injuryprev-2016-04204510.1136/injuryprev-2016-042045]Search in Google Scholar
[11. Bared, J.G., Vogt, A., 1998. Accident models for two-lane rural roads: segments and intersections. Federal Highway Administration.]Search in Google Scholar
[12. Bhatia, R., Wier, M., Weintraub, J., Humphreys, E.H., Seto, E., 2009. An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accid. Anal. Prev. doi:10.1016/j.aap.2008.10.00110.1016/j.aap.2008.10.001]Open DOISearch in Google Scholar
[13. Broughton, J., 1991. Forecasting road accident casualties in Great Britain. Accid. Anal. Prev. 23 5, 353–362.10.1016/0001-4575(91)90056-B]Search in Google Scholar
[14. Budzynski, M., Jamroz, K., Kustra, W., Gaca, S., Michalski, L., 2011. Instructions for road safety auditors – Part One Assessing the effects of road infrastructure projects on road safety, Part Two Road safety audit – for the GDDKiA. Gdansk University of Technology, Krakow University of Technology, Gdansk.]Search in Google Scholar
[15. Budzynski, M., Jamroz, K., Kustra, W., Zukowska, J., 2015. Modeling of traffic safety indicators on Polish national road network, in: Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015. pp. 23–30.10.1201/b19094-6]Search in Google Scholar
[16. Budzynski, M., Kustra, W., Jamroz, K., Gaca, S., Michalski, L., Guminska, L., 2013. Method for forecasting road safety indicators for the purposes of economic effectiveness analyses for projects on Poland’s national roads – for the GDDKiA. Gdansk University of Technology, Krakow University of Technology, Gdansk.]Search in Google Scholar
[17. Budzynski, M., Rys, D., Kustra, W., 2017. Selected Problems of Transport in Port Towns - Tri-City as an Example. Polish Marit. Res. 24 s1, 16–24. doi:10.1515/pomr-2017-001610.1515/pomr-2017-0016]Open DOISearch in Google Scholar
[18. Cafiso, S., Di Graziano, A., Di Silvestro, G., La Cava, G., Persaud, B., 2010. Development of comprehensive accident models for two-lane rural highways using exposure, geometry, consistency and context variables. Accid. Anal. Prev. 42 4, 1072–9. doi:10.1016/j.aap.2009.12.01510.1016/j.aap.2009.12.015]Open DOISearch in Google Scholar
[19. Council, F.M., Harwood, D.W., Hauer, E., Hughes, W.E., Vogt, A., 2000. Prediction of the Expected Safety Performance of Rural Two-Lane Highways. Federal Highway Administration.]Search in Google Scholar
[20. Deffenbacher, J.L., Lynch, R.S., Filetti, L.B., Dahlen, E.R., Oetting, E.R., 2003. Anger, aggression, risky behavior, and crash-related outcomes in three groups of drivers. Behav. Res. Ther. 41, 333–349. doi:10.1016/S0005-7967(02)00014-110.1016/S0005-7967(02)00014-1]Open DOISearch in Google Scholar
[21. Donmez, B., Boyle, L.N., Lee, J.D., 2007. Safety implications of providing real-time feedback to distracted drivers. Accid. Anal. Prev. 39 3, 581–590. doi:10.1016/J.AAP.2006.10.00310.1016/J.AAP.2006.10.003]Open DOISearch in Google Scholar
[22. El-Basyouny, K., Sayed, T., 2009. Accident prediction models with random corridor parameters. Accid. Anal. Prev. 41 5, 1118–23. doi:10.1016/j.aap.2009.06.02510.1016/j.aap.2009.06.02519664455]Open DOISearch in Google Scholar
[23. Elvik, R., 2008. The predictive validity of empirical Bayes estimates of road safety. Accid. Anal. Prev. 40 6, 1964–9. doi:10.1016/j.aap.2008.07.00710.1016/j.aap.2008.07.00719068301]Open DOISearch in Google Scholar
[24. Fernandes, A., Neves, J., 2013a. An approach to accidents modeling based on compounds road environments. Accid. Anal. Prev. 53 2013, 39–45. doi:10.1016/j.aap.2012.12.04110.1016/j.aap.2012.12.04123376544]Open DOISearch in Google Scholar
[25. Fernandes, A., Neves, J., 2013b. An approach to accidents modeling based on compounds road environments. Accid. Anal. Prev. 53 2013, 39–45. doi:10.1016/j.aap.2012.12.04110.1016/j.aap.2012.12.041]Open DOISearch in Google Scholar
[26. Garber, N.J., Lei, W., 2001. Stochastic Models Relating Crash Probabilities With Geometric And Corresponding Traffic Characteristics Data. University of Virginia, Charlottesville.]Search in Google Scholar
[27. Geedipally, S.R., Lord, D., Dhavala, S.S., 2012a. The negative binomial-Lindley generalized linear model: characteristics and application using crash data. Accid. Anal. Prev. 45 2012, 258–65. doi:10.1016/j.aap.2011.07.01210.1016/j.aap.2011.07.01222269508]Open DOISearch in Google Scholar
[28. Geedipally, S.R., Lord, D., Dhavala, S.S., 2012b. The negative binomial-Lindley generalized linear model: characteristics and application using crash data. Accid. Anal. Prev. 45 2012, 258–65. doi:10.1016/j.aap.2011.07.01210.1016/j.aap.2011.07.012]Open DOISearch in Google Scholar
[29. Hakkert, S., 2011. EuroRAP evaluation experience alongside other measures in Israel, in: EuroRAP Plenary, Policy Seminar and Training Course, Belgrade.]Search in Google Scholar
[30. Hauer, E., 2007. Safety Models for Urban Four-lane Undivided Road Segments. Transp. Res. Rec. J. Transp. Res. Board 96–105, 1–22.10.3141/1897-13]Search in Google Scholar
[31. Hauer, E., 2004. Statistical Road Safety Modeling. Transp. Res. Rec. J. Transp. Res. Board 1897 May, 81–87. doi:10.3141/1897-1110.3141/1897-11]Open DOISearch in Google Scholar
[32. Hauer, E., 2001. Overdispersion in modelling accidents on road sections and in empirical bayes estimation. Accid. Anal. Prev. 33 6, 799–808.10.1016/S0001-4575(00)00094-4]Search in Google Scholar
[33. Hauer, E., 1995. On exposure and accident rate. Traffic Eng. Control 36, 134–138.]Search in Google Scholar
[34. Hauer, E., 1986. On the estimation of the expected number of accidents. Accid. Anal. Prev. 18 1, 1–12. doi:10.1016/0001-4575(86)90031-X10.1016/0001-4575(86)90031-X]Open DOISearch in Google Scholar
[35. Hewson, P., 2004. Deprived children or deprived neighbourhoods? A public health approach to the investigation of links between deprivation and injury risk with specific reference to child road safety in Devon County, UK. BMC Public Health 4, 15. doi:10.1186/1471-2458-4-1510.1186/1471-2458-4-1541935615134585]Open DOISearch in Google Scholar
[36. Ivan, J.N., Garder, P.E., Deng, Z., Zhang, C., 2006. The effect of segment characteristics on the severity of head-on crashes on two-lane rural highways. University of Connecticut, University of Maine.]Search in Google Scholar
[37. Ivan, J.N., Lord, D., Washington, S.P., 2005. Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory. Accid. Anal. Prev. 37 1, 35–46. doi:10.1016/j.aap.2004.02.00410.1016/j.aap.2004.02.00415607273]Open DOISearch in Google Scholar
[38. Iyinam, A.F., Iyinam, S., Ergun, M., 1997. Analysis of Relationship Between HighwaySafety and Road Geometric Design Elements : Turkish Case. Technical University of Istanbul.]Search in Google Scholar
[39. Jamroz, K., 2011. Method of risk management in highway engineering. Gdansk University of Technology, Gdansk.]Search in Google Scholar
[40. Jamroz, K., Kustra, W., 2011. The risk atlas of Poland’s national roads 2008-2010. Foundation for Development of Civil Engineering, Gdansk.]Search in Google Scholar
[41. Jurewicz, C., Steinmetz, L., 2012. Crash performance of safety barriers on high - speed roads. J. Australas. Coll. Road Saf. 23 3.]Search in Google Scholar
[42. Kiec, M., 2009. The impact of the accessibility of the road on conditions and traffic safety - PhD thesis. Cracow University of Technology.]Search in Google Scholar
[43. Kustra, W., 2016. Modelling selected road safety measures on long road sections - thesis.]Search in Google Scholar
[44. Kustra, W., Budzynski, M., Jamroz, K., Zukowska, J., 2015. Modelling of traffic safety indicators on Polish national road network, in: ESREL 2015 25th European Safety and Reliability Conference. Zurich, p. 7.10.1201/b19094-6]Search in Google Scholar
[45. Lao, Y., Wu, Y.-J., Corey, J., Wang, Y., 2011a. Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression. Accid. Anal. Prev. 43 1, 220–7. doi:10.1016/j.aap.2010.08.01310.1016/j.aap.2010.08.01321094317]Open DOISearch in Google Scholar
[46. Lao, Y., Wu, Y.-J., Corey, J., Wang, Y., 2011b. Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression. Accid. Anal. Prev. 43 1, 220–7. doi:10.1016/j.aap.2010.08.01310.1016/j.aap.2010.08.013]Open DOISearch in Google Scholar
[47. Lee, C., Hellinga, B., Saccomanno, F., 2006. Evaluation of variable speed limits to improve traffic safety. Transp. Res. Part C Emerg. Technol. 14 3, 213–228. doi:10.1016/J.TRC.2006.06.00210.1016/J.TRC.2006.06.002]Open DOISearch in Google Scholar
[48. Lee, J., Mannering, F., 2002. Impact of roadside features on the frequency and severity of run-off-roadway accidents: an empirical analysis. Accid. Anal. Prev. 34 2, 149–61.10.1016/S0001-4575(01)00009-4]Search in Google Scholar
[49. Li, R., Shang, P., 2014. Incident duration modeling using flexible parametric hazard-based models. Comput. Intell. Neurosci. 2014, 723427. doi:10.1155/2014/72342710.1155/2014/723427]Search in Google Scholar
[50. Litman, T., 2010. Transportation Elasticities, Transportation. Victoria Transport Policy Institute, Victoria.]Search in Google Scholar
[51. Lord, D., 2006. Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter. Accid. Anal. Prev. 38 4, 751–66. doi:10.1016/j.aap.2006.02.00110.1016/j.aap.2006.02.001]Open DOISearch in Google Scholar
[52. Lord, D., Geedipally, S.R., 2012. Examining the Crash Variances Estimated by the Poisson-Gamma and Conway-Maxwell-Poisson Models. Transp. Res. Rec. J. Transp. Res. Board 2241 979, 56–67.10.3141/2241-07]Search in Google Scholar
[53. Lord, D., Park, B., 2012. Negative Binomial Regression Models and Estimation Methods, in: Probability Density and Likelihood Functions. Texas A&M University, Korea Transport Institute, pp. 1–15.]Search in Google Scholar
[54. Lord, D., Park, P.Y.-J., 2008. Investigating the effects of the fixed and varying dispersion parameters of Poisson-gamma models on empirical Bayes estimates. Accid. Anal. Prev. 40 4, 1441–57. doi:10.1016/j.aap.2008.03.01410.1016/j.aap.2008.03.014]Open DOISearch in Google Scholar
[55. Ma, J., Kockelman, K.M., Damien, P., 2008a. A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. Accid. Anal. Prev. 40 3, 964–75. doi:10.1016/j.aap.2007.11.00210.1016/j.aap.2007.11.002]Open DOISearch in Google Scholar
[56. Ma, J., Kockelman, K.M., Damien, P., 2008b. A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. Accid. Anal. Prev. 40 3, 964–75. doi:10.1016/j.aap.2007.11.00210.1016/j.aap.2007.11.002]Open DOISearch in Google Scholar
[57. Mannering, F., Venkataraman, S., Woodrow, B., 1996. Statistical analysis of accident rural freeways. Accid. Anal. Prev. 28 3, 391–401.10.1016/0001-4575(96)00009-7]Search in Google Scholar
[58. Martinelli, F., La Torre, F., Vadi, P., 2009. Calibration of the Highway Safety Manual’s Accident Prediction Model for Italian Secondary Road Network. Transp. Res. Rec. J. Transp. Res. Board 2103, 1–9. doi:10.3141/2103-0110.3141/2103-01]Open DOISearch in Google Scholar
[59. Peer, E., Rosenbloom, T., 2013. When two motivations race: The effects of time-saving bias and sensation-seeking on driving speed choices. Accid. Anal. Prev. 50, 1135–1139. doi:10.1016/J.AAP.2012.09.00210.1016/J.AAP.2012.09.00223021421]Open DOISearch in Google Scholar
[60. Ptak-Chmielewska, A., 2013. Generalised linear models. Warsaw School of Economic, Warsaw.]Search in Google Scholar
[61. Rakha, H., Arafeh, M., Abdel-Salam, A.G., Guo, F., Flintsch, A.M., 2010. Linear regression crash prediction models: issues and proposed solutions, Virginia Tech Transportation Institute.]Search in Google Scholar
[62. Reurings, M., Jannsen, T., Eenink, R., Elvik, R., Cardoso, J., Stefan, C., 2005. Accident Prediction Models and Road Safety Impact Assessment a state of the art, Ripcord. Ripcord - Iserest.]Search in Google Scholar
[63. Ryb, G.E., Dischinger, P.C., Kleinberger, M., McGwin, G., Griffin, R.L., 2013. Aortic injuries in newer vehicles. Accid. Anal. Prev. 59, 253–259. doi:10.1016/J.AAP.2013.06.00710.1016/J.AAP.2013.06.00723831451]Open DOISearch in Google Scholar
[64. Schafer, J., 2006. Penn State Department of Statistics [WWW Document]. Dep. Stat. Eberly Coll. Sci. URL sites. stat.psu.edu]Search in Google Scholar
[65. Scott-Parker, B., Watson, B., King, M., Hyde, M., 2012. Young, Inexperienced, and on the Road. Transp. Res. Rec. J. Transp. Res. Board. doi:10.3141/2318-1210.3141/2318-12]Open DOISearch in Google Scholar
[66. Son, H. “Daniel,” Kweon, Y.-J., Park, B. “Brian,” 2011. Development of crash prediction models with individual vehicular data. Transp. Res. Part C Emerg. Technol. 19 6, 1353–1363. doi:10.1016/j.trc.2011.03.00210.1016/j.trc.2011.03.002]Open DOISearch in Google Scholar
[67. Technical Committee 18, 2004. Study on Risk Management for Roads. PIARC.]Search in Google Scholar
[68. The National Police Headquarters, 2015. SEWIK - Accident data base.]Search in Google Scholar
[69. Vaziri, M., 2010. A comparative appraisal of roadway accident for Asia-Pacific countries. Int. J. Eng. Trans. A Basics 23 2, 111–126.]Search in Google Scholar
[70. Wood, G.R., 2005. Confidence and prediction intervals for generalised linear accident models. Accid. Anal. Prev. 37 2, 267–73. doi:10.1016/j.aap.2004.10.00510.1016/j.aap.2004.10.00515667813]Open DOISearch in Google Scholar
[71. Xie, K., Wang, X., Huang, H., Chen, X., 2013. Corridor-level signalized intersection safety analysis in Shanghai, China using Bayesian hierarchical models. Accid. Anal. Prev. 50, 25–33. doi:10.1016/J.AAP.2012.10.00310.1016/J.AAP.2012.10.00323149321]Open DOISearch in Google Scholar
[72. Yannis, G., Papadimitriou, E., Chaziris, A., Broughton, J., 2014. Modeling road accident injury under-reporting in Europe. Eur. Transp. Res. Rev. 6 4, 425–438. doi:10.1007/s12544-014-0142-410.1007/s12544-014-0142-4]Open DOISearch in Google Scholar
[73. Ye, Z., Zhang, Y., Lord, D., 2013a. Goodness-of-fit testing for accident models with low means. Accid. Anal. Prev. 61, 78–86. doi:10.1016/j.aap.2012.11.00710.1016/j.aap.2012.11.00723219076]Open DOISearch in Google Scholar
[74. Ye, Z., Zhang, Y., Lord, D., 2013b. Goodness-of-fit testing for accident models with low means. Accid. Anal. Prev. 61, 78–86. doi:10.1016/j.aap.2012.11.00710.1016/j.aap.2012.11.007]Open DOISearch in Google Scholar
[75. Zhang, W., Huang, Y.-H., Roetting, M., Wang, Y., Wei, H., 2006. Driver’s views and behaviors about safety in China—What do they NOT know about driving? Accid. Anal. Prev. 38 1, 22–27. doi:10.1016/J.AAP.2005.06.01510.1016/J.AAP.2005.06.015]Open DOISearch in Google Scholar