1. Soltani N, Mamdoohi AR. A model of driver behavior in response to road roughness: A case study of Yazd arterials. J Geotechnical Transp Eng 2016;2:45-50.
2. Naderan A, Shahi J. Aggregate crash prediction models: Introducing crash generation concept. Accid Anal Prev 2010;42:339‑46.
3. Elmitiny N, Yan X, Radwan E, Russo C, Nashar D. Classification analysis of driver’s stop/go decision and red‑light running violation. Accid Anal Prev 2010;42:101‑11.
4. Köll H, Bader M, Axhausen KW. Driver behaviour during flashing green before amber: A comparative study. Accid Anal Prev 2004;36:273‑80.
5. Papaioannou P. Driver behaviour, dilemma zone and safety effects at urban signalized intersections in Greece. Accid Anal Prev 2007;39:147‑58.
6. Cai Q, Lee J, Eluru N, Abdel‑Aty M. Macro‑level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models. Accid Anal Prev 2016;93:14‑22.
7. Miaou SP. The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions. Accid Anal Prev 1994;26:471‑82.
8. El‑Basyouny K, Sayed T. Accident prediction models with random corridor parameters. Accid Anal Prev 2009;41:1118‑23.
9. Qin X, Ivan JN, Ravishanker N. Selecting exposure measures in crash rate prediction for two‑lane highway segments. Accid Anal Prev 2004;36:183‑91. 10. Zeng Q, Wen H, Huang H, Pei X, Wong SC. A multivariate random‑parameters Tobit model for analyzing highway crash rates by injury severity. Accid Anal Prev 2017;99:184‑91.
11. Park BJ, Lord D, Hart JD. Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis. Accid Anal Prev 2010;42:741‑9.
12. Xie K, Wang X, Huang H, Chen X. Corridor‑level signalized intersection safety analysis in Shanghai, China using Bayesian hierarchical models. Accid Anal Prev 2013;50:25‑33.
13. Lee J, Abdel‑Aty M, Choi K, Huang H. Multi‑level hot zone identification for pedestrian safety. Accid Anal Prev 2015;76:64‑73.
14. Lord D, Mannering F. The statistical analysis of crash‑frequency data: A review and assessment of methodological alternatives. Transp Res Part A Policy Pract 2010;44:291‑305.
15. Mannering FL, Bhat CR. Analytic methods in accident research: Methodological frontier and future directions. Anal Methods Accident Res 2014;1:1‑22.
16. Anastasopoulos PC, Mannering FL. A note on modeling vehicle accident frequencies with random‑parameters count models. Accid Anal Prev 2009;41:153‑9.
17. Lord D, Guikema SD, Geedipally SR. Application of the Conway‑Maxwell‑Poisson generalized linear model for analyzing motor vehicle crashes. Accid Anal Prev 2008;40:1123‑34.
18. Couto A, Ferreira S. A note on modeling road accident frequency: A flexible elasticity model. Accid Anal Prev 2011;43:2104‑11.
19. Quddus MA. Modelling area‑wide count outcomes with spatial correlation and heterogeneity: An analysis of London crash data. Accid Anal Prev 2008;40:1486‑97.
20. Hadayeghi A, Shalaby AS, Persaud BN. Development of planning level transportation safety tools using Geographically Weighted Poisson Regression. Accid Anal Prev 2010;42:676‑88.
21. Abdel‑Aty M, Siddiqui C, Huang H, Wang X. Integrating trip and roadway characteristics to manage safety in traffic analysis zones. Transp Res Record J Transp Res Board 2011;22:20‑8.
22. Pulugurtha SS, Duddu VR, Kotagiri Y. Traffic analysis zone level crash estimation models based on land use characteristics. Accid Anal Prev 2013;50:678‑87.
23. Xu P, Huang H. Modeling crash spatial heterogeneity: Random parameter versus geographically weighting. Accid Anal Prev 2015;75:16‑25.
24. Gelman A, Hill J. Data Analysis using Regression and Multilevel Hierarchical Models. New York, USA: Cambridge University Press; 2007.
25. Dupont E, Papadimitriou E, Martensen H, Yannis G. Multilevel analysis in road safety research. Accid Anal Prev 2013;60:402‑11.
26. Shi Q, Abdel‑Aty M, Yu R. Multi‑level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway. Accid Anal Prev 2016;88:68‑76.
27. Karaboga D. An Idea Based on Honey Bee Swarm for Numerical Optimization. Technical Report‑tr06, Erciyes University, Engineering Faculty, Computer Engineering Department; 2005.
28. Yang XS, Deb S. Cuckoo search via lévy flights. In: Proceedings of the Nature and Biologically Inspired Computing, 2009. NaBIC. World Congress on; 2009. p. 210‑4.
29. Mirjalili S. The ant lion optimizer. Adv Eng Software 2015;83:80‑98.
30. Wang GG, Guo L, Gandomi AH, Hao GS, Wang H. Chaotic krill herd algorithm Inf Sci 2014;274:17‑34.
31. Guo L, Wang GG, Gandomi AH, Alavi AH, Duan H. A new improved krill herd algorithm for global numerical optimization Neurocomputing 2014;138:392‑402.
32. Wang GG, Deb S, Coelho L. Earthworm optimization algorithm: A bioinspired metaheuristic algorithm for global optimization problems. International Journal of Bio-Inspired Computation 2018;12:1-22.
33. Rashedi E, Nezamabadi‑Pour H, Saryazdi S. Gsa: A gravitational search algorithm. Inf Sci 2009;179:2232‑48.
34. Feng Y, Wang GG, Deb S, Lu M, Zhao XJ. Solving 0‑1 knapsack problem by a novel binary monarch butterfly optimization. Neural Comput Applicat 2017;28:1619‑34.
35. Wang GG, Deb S, Coelho LD. Elephant herding optimization. 3rd International Symposium on Computational and Business Intelligence (ISCBI), Bali, Indonesia, 2015:1-5.
36. Wang GG, Deb S, Gao XZ, Coelho LD. Anew metaheuristic optimisation algorithm motivated by elephant herding behaviour. Int J Bio Inspired Comput 2016;8:394‑409.
37. Mirjalili S, Mirjalili SM, Lewis A. Grey wolf optimizer. Adv Eng Software 2014;69:46‑61.
38. Shobeiri V. The optimal design of structures using ACO and EFG. Eng Comput 2016;32:645‑53.
39. Fabritius B, Tabor G. Improving the quality of finite volume meshes through genetic optimisation. Eng Comput 2016;32:425‑40.
40. PuthaR, QuadrifoglioL, ZechmanE. Comparing ant colony optimization and genetic algorithm approaches for solving traffic signal coordination under oversaturation conditions. Comput Aided Civil Infrastructure Eng 2012;27:14‑28.
41. Abbas M, Bullock D, Head L. Real‑time offset transitioning algorithm for coordinating traffic signals. Transp Res Record J Transp Res Board 2001;1748:26‑39.
42. He J, Hou Z. Ant colony algorithm for traffic signal timing optimization. Adv Eng Software 2012;43:14‑8.
43. Lee J, Kim J, Park BB. A genetic algorithm‑based procedure for determining optimal time‑of‑day break points for coordinated actuated traffic signal systems. KSCE J Civil Eng 2011;15:197‑203.
44. Lin DY, Ku YH. Using genetic algorithms to optimize stopping patterns for passenger rail transportation. Comput Aided Civil Infrastructure Eng 2014;29:264‑78.
45. PeñabaenaNiebles R, Cantillo V, Moura JL, Ibeas A. Design and evaluation of a mathematical optimization model for traffc signal plan transition based on social cost function. Journal of Advanced Transportation 2017:1-12.
46. Abbas KA. Traffic safety assessment and development of predictive models for accidents on rural roads in Egypt. Accid Anal Prev 2004;36:149‑63. 47. Greibe P. Accident prediction models for urban roads. Accid Anal Prev 2003;35:273‑85.
48. Gujarati DN. Basic Econometrics. New York, Tata McGrawHill Education; 2009
49. Jones K. Using multilevel models for survey analysis. J Market Res Soc 1993;35:249.
50. Huang H, Zhou H, Wang J, Chang F, Ma M. Amultivariate spatial model of crash frequency by transportation modes for urban intersections. Anal Methods Accident Res 2017;14:10‑21.
51. Varaee H, Ghasemi MR. Engineering optimization based on ideal gas molecular movement algorithm. Eng Comput 2017;33:71‑93.