Severity analysis of crashes on express lane facilities using support vector machine model trained by firefly algorithm

References

• Alluri P, Sando T, Kadeha C, Haule H, Salum J, Ali MS, Kodi J, Kitali A. 2020. Developing Florida-specific Mobility Enhancement Factors (MEFs) and Crash Modification Factors (CMFs) for TSM&O strategies. Tallahassee, Florida: Florida Department of Transportation.
   Google Scholar
• Anderson J, Hernandez S. 2017. Roadway classifications and the accident injury severities of heavy-vehicle drivers. Anal Methods Accid Res. 15:17–28.
   Web of Science ®Google Scholar
• Chen C, Zhang G, Liu XC, Ci Y, Huang H, Ma J, Chen Y, Guan H. 2016. Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation. Accid Anal Prev. 97:69–78. doi:10.1016/j.aap.2016.07.031
   PubMed Web of Science ®Google Scholar
• Chen C, Zhang G, Qian Z, Tarefder RA, Tian Z. 2016. Investigating driver injury severity patterns in rollover crashes using support vector machine models. Accid Anal Prev. 90:128–139. doi:10.1016/j.aap.2016.02.011
   PubMed Web of Science ®Google Scholar
• Cortes C, Vapnik V. 1995. Support-vector networks. Mach Learn. 20(3):273–297.
   Web of Science ®Google Scholar
• Eisele WL, Wilner HT, Bolin MJ, Stockton WR, Burris MW, Goodin GD, Collier T, Winn J, Xu L, Hoelscher M. 2006. Evaluation criteria for adapting HOV lanes to HOT lanes: Development and application of HOT start software tool (FHWA/TX-06/0-4898-1). Austin, TX: Texas Department of Transportation.
   Google Scholar
• FHWA. 2008. Managed lanes primer (FHWA-HOP-05-031). Washington (DC): FHWA.
   Google Scholar
• Huang H, Chin HC, Haque MM. 2008. Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis. Accid Anal Prev. 40(1):45–54. doi:10.1016/j.aap.2007.04.002
   PubMed Web of Science ®Google Scholar
• IIHS-HLDI. 2018. Fatality facts. Insurance Institute for Highway Safety: Highway loss data. [accessed 2018 June 9]. https://www.iihs.org/iihs/topics/t/general-statistics/fatalityfacts/state-by-state-overview.
   Google Scholar
• Kadeha C, Alluri P, Sando T. 2020. Quantifying the mobility benefits of express lanes using real-time traffic data. Transp Res Rec. doi:10.1177/0361198120947091.
   Web of Science ®Google Scholar
• Kuhn B, Goodin G, Ballard A, Brewer M, Brydia R, Carson J, Chrysler S, Collier T, Fitzpatrick K, Jasek D, et al. 2005. Managed lanes handbook (FHWA/TX-06/0-4160-24). Texas: Texas Transportation Institute.
   Google Scholar
• Machumu KS, Sando T, Mtoi E. 2017. Establishing the minimum routing decision distance for express lanes. Adv Transp Stud. 43:17–30.
   Google Scholar
• Mokhtarimousavi S, Anderson JC, Azizinamini A, Hadi M. 2019. Improved support vector machine models for work zone crash injury severity prediction and analysis. Transp Res Rec. 2673(11):680–692.
   Web of Science ®Google Scholar
• Salum JH, Kitali AE, Bwire H, Sando T, Alluri P. 2019. Severity of motorcycle crashes in Dar es Salaam, Tanzania. Traffic Inj Prev. 20(2):1–7.
   Web of Science ®Google Scholar
• Shen L, Chen H, Yu Z, Kang W, Zhang B, Li H, Yang B, Liu D. 2016. Evolving support vector machines using fruit fly optimization for medical data classification. Knowledge-Based Syst. 96:61–75.
   Web of Science ®Google Scholar
• Srinivasan S, Haas P, Alluri P, Gan A, Bonneson J. 2015. Crash prediction method for freeway facilities with High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT) lanes (BDV32-977-04). Tallahassee (Florida): Dept. of Transportation.
   Google Scholar
• Uddin M, Huynh N. 2018. Factors influencing injury severity of crashes involving HAZMAT trucks. Int J Transp Sci Technol. 7(1):1–9.
   Google Scholar
• Yang XS. 2008. Nature-inspired metaheuristic algorithms. Cambridge (United Kingdom): Luniver Press.
   Google Scholar
• Yu R, Abdel-Aty M. 2013. Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes. Accid Anal Prev. 58:97–105. doi:10.1016/j.aap.2013.04.025
   PubMed Web of Science ®Google Scholar
• Zeng Q, Wen H, Huang H, Abdel-Aty M. 2017. A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments. Accid Anal Prev. 100:37–43. doi:10.1016/j.aap.2016.12.023
   PubMed Web of Science ®Google Scholar