Safety features of freeway weaving segments with a buffer-separated high-occupancy-vehicle (HOV) lane

References

• ASSHTO Subcommittee on Design. (October 2004). Guide for high occupancy vehicle facilities. Washington, DC: American Association of State Highway and Transportation Officials.
   Google Scholar
• Cheng, L., Geedipally, S.R., & Lord, D. (2013). Examining the Poisson-Weibull generalized linear model for analyzing crash data. Safety Science, 54, 38–42.
   Web of Science ®Google Scholar
• Cirillo, J.A. (1970). The relationship of accidents to length of speed-change lanes and weaving areas on interstate highways. Highway Research Record, 312, 17–32.
   Google Scholar
• Connors, R.D., Maher, M., Wood, A., Mountain, L., & Ropkins, K. (2013). Methodology for fitting and updating predictive accident models with trend. Accident Analysis and Prevention, 56, 82–94.
   PubMed Web of Science ®Google Scholar
• Cooner, S.A., & Ranft, S.E. (2006). Safety evaluation of buffer-separated high-occupancy vehicle lanes in Texas. Transportation Research Record, 1959, 168–177.
   Google Scholar
• Federal Highway Administration. (2011). Highway safety information system (Report No. FHWA-HRT-11-031). Washington, DC.
   Google Scholar
• Garber, N.J., & Gadiraju, R. (1989). Factors affecting speed variance and its influence on accidents. Transportation Research Record, 1213, 64–71.
   Google Scholar
• Golembiewski, G.A., & Chandler, B. (2011). Roadway departure safety: A manual for local rural road owners (Report No. FHWA-SA-11-09). Washington, DC: Federal Highway Administration.
   Google Scholar
• Golob, T.F., Recker, W.W., & Alvarez, V.M. (2004). Safety aspects of freeway weaving sections. Transportation Research Part A, 38, 35–51.
   Google Scholar
• Golob, T.F., Recker, W.W., & Levine, D.W. (1989). Safety of high-occupancy vehicle lanes without physical separation. Journal of Transportation Engineering, 115, 591–607.
   Google Scholar
• Hauer, E. (1997). Observational before-after studies in road safety. Oxford: Pergamon Press, Elsevier Science Ltd.
   Google Scholar
• Jang, K., Chung, K., Ragland, D.R., & Chan, C.-Y. (2009). Safety performance of high-occupancy-vehicle facilities. Transportation Research Record, 2099, 132–140.
   Google Scholar
• Lee, J., Dittberner, R., & Sripathi, H. (2007). Safety impacts of freeway managed-lane strategy. Transportation Research Record, 2012, 113–120.
   Google Scholar
• Lee, C., Saccomanno, F., & Hellinga, B. (2002). Analysis of crash precursors on instrumented freeways. Transportation Research Record, 1784, 1–8.
   Google Scholar
• Liu, P., Chen, H., Lu, J.J., & Cao, B. (2010). How lane arrangements on freeway mainlines and ramps affect safety of freeways with closely spaced entrance and exit ramps. Journal of Transportation Engineering, 136, 614–622.
   Web of Science ®Google Scholar
• 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. Accident Analysis and Prevention, 38(4), 751–766.
   PubMed Web of Science ®Google Scholar
• Lord, D., Manar, A., & Vizioli, A. (2005). Modeling crash-flow-density and crash-flow-V/C ratio relationships for rural and urban freeway segments. Accident Analysis and Prevention, 37(1), 185–199
   PubMed Web of Science ®Google Scholar
• Lord, D., & Miranda-Moreno, L.F. (2008). Effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter of Poisson-gamma models for modeling motor vehicle crashes: A Bayesian perspective. Safety Science, 46(5), 751–770.
   Web of Science ®Google Scholar
• Lunn, D.J., Thomas, A., Best, N., & Spiegelhalter, D. (2000). WinBUGS – a Bayesian modelling framework: Concepts, structure, and extensibility. Statistics and Computing, 10(4), 325–337.
   Web of Science ®Google Scholar
• Maher, M.J., & Mountain, L.J. (2009). The sensitivity of estimates of regression to the mean. Accident Analysis and Prevention, 41, 861–868.
   PubMed Web of Science ®Google Scholar
• Martin, J.-L. (2002). Relationship between crash rate and hourly traffic flow on interurban motorways. Accident Analysis and Prevention, 34, 619–629.
   PubMed Web of Science ®Google Scholar
• Mitra, S., & Washington, S. (2007). On the nature of over-dispersion in motor vehicle crash prediction models. Accident Analysis and Prevention, 39(3), 459–468.
   PubMed Web of Science ®Google Scholar
• Pulugurtha, S.S., & Bhatt, J. (2010). Evaluating the role of weaving section characteristics and traffic on crashes in weaving areas. Traffic Injury Prevention, 11, 104–113.
   PubMed Web of Science ®Google Scholar
• R Development Core Team. (2006). R: A language and environment for statistical computing., Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org.
   Google Scholar
• Sullivan, E.C., & Devadoss, N. (1993). High-occupancy vehicle facility safety in California. Transportation Research Record, 1394, 49–58.
   Google Scholar
• Varaiya, P. (2009). The freeway performance measurement system (PeMS) (PeMS 9.0: Final Report). California PATH Research Report (Report No. UCB-ITS-PRR-2009-25). Berkeley, CA: Institute of Transportation Studies, University of California.
   Google Scholar
• Wang, L., Abdel-Aty, M., Shi, Q., & Park, J. (2015). Real-time crash prediction for expressway weaving segments. Transportation Research Part C, 61, 1–10.
   Web of Science ®Google Scholar
• Wang, C., Quddus, M.A., & Ison, S.G. (2009). Impact of traffic congestion on road accidents_A spatial analysis of the M25 motorway in England. Accident Analysis and Prevention, 41, 798–808.
   PubMed Web of Science ®Google Scholar