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Articles

Development of crash modification factors for intersections in Toowoomba city

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Pages 104-123 | Received 10 Dec 2018, Accepted 04 Mar 2020, Published online: 23 Mar 2020

References

  • AASHTO. (2010). Highway safety manual (1st ed.). Washington, DC: American Association of State Highway and Transportation Officials.
  • Abdel-Aty, M., Lee, C., Park, J., Wang, J., Abuzwidah, M., & Al-Arifi, S. (2014). Validation and application of highway safety manual (Part D) in Florida. Orlando, FL. Retrieved from Final Report.
  • Abdel-Aty, M., & Radwan, E. (2000). Modeling traffic accident occurrence and involvement. Accident Analysis & Prevention, 32(5), 633–642. doi: 10.1016/S0001-4575(99)00094-9
  • Abdul Manan, M. M., Jonsson, T., & Várhelyi, A. (2013). Development of a safety performance function for motorcycle accident fatalities on Malaysian primary roads. Safety Science, 60, 13–20. doi: 10.1016/j.ssci.2013.06.005
  • Ackaah, W., & Salifu, M. (2011). Crash prediction model for two-lane rural highways in the Ashanti region of Ghana. IATSS Research, 35(1), 34–40. doi: 10.1016/j.iatssr.2011.02.001
  • Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. doi: 10.1109/TAC.1974.1100705
  • Bahar, G. (2010). Methodology for the development and inclusion of crash modification factors in the first edition of the highway safety manual (Report No. Transportation Research Circular E-C142). Washington, DC: T. R. Board.
  • Bauer, K. M., & Harwood, D. W. (2000). Statistical models of At-grade intersection accidents – Addendum (Report No. FHWA-RD-99-094). Georgetown Pike.
  • BITRE. (2015). Road trauma Australia. Retrieved from http://bitre.gov.au/publications/ongoing/road_deaths_Australia_annual_summaries.aspx
  • Bonneson, J. A., & Lord, D. (2005). Role and application of accident modification factors in the highway design process (Report No. FHW A/TX-05/0-4703-2). Texas.
  • Bonneson, J. A., & Pratt, M. P. (2009). Roadway safety design workbook (Report No. FHWA/TX-09/0-4703-P2). Texas.
  • 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. Accident Analysis & Prevention, 42(4), 1072–1079. doi: 10.1016/j.aap.2009.12.015
  • Caliendo, C., Guida, M., & Parisi, A. (2007). A crash-prediction model for multilane roads. Accident Analysis & Prevention, 39(4), 657–670. doi: 10.1016/j.aap.2006.10.012
  • Chen, H., Cao, L., & Logan, D. B. (2012). Analysis of risk factors affecting the severity of intersection crashes by logistic regression. Traffic Injury Prevention, 13(3), 300–307. doi: 10.1080/15389588.2011.653841
  • Chin, H. C., & Quddus, M. A. (2003). Applying the random effect negative binomial model to examine traffic accident occurrence at signalized intersections. Accident Analysis & Prevention, 35(2), 253–259. doi: 10.1016/S0001-4575(02)00003-9
  • Corben, B. F., & Wai, F. C. (1990). Pro-active traffic engineering safety study, final report: Part 2-right-turn-against crashes at traffic signals (Report No. 11).
  • Da Costa, S., Qu, X., & Parajuli, P. M. (2015). A crash severity-based black spot identification model. Journal of Transportation Safety & Security, 7(3), 268–277. doi: 10.1080/19439962.2014.911230
  • Elvik, R. (2007). State-of-the-art approaches to road accident black spot management and safety analysis of road networks (Report No. 883).
  • Elvik, R. (2008). Comparative analysis of techniques for identifying locations of hazardous roads. Transportation Research Record, 2083, 72–75. doi: 10.3141/2083-08
  • Elvik, R., Ulstein, H., Wifstad, K., Syrstad, R. S., Seeberg, A. R., Gulbrandsen, M. U., & Welde, M. (2017). An Empirical Bayes before-after evaluation of road safety effects of a new motorway in Norway. Accident Analysis & Prevention, 108, 285–296. doi: 10.1016/j.aap.2017.09.014
  • Elvik, R., Vadeby, A., Hels, T., & van Schagen, I. (2019). Updated estimates of the relationship between speed and road safety at the aggregate and individual levels. Accident Analysis & Prevention, 123, 114–122. doi: 10.1016/j.aap.2018.11.014
  • Fawcett, L., Thorpe, N., Matthews, J., & Kremer, K. (2017). A novel Bayesian hierarchical model for road safety hotspot prediction. Accident Analysis & Prevention, 99, 262–271. doi: 10.1016/j.aap.2016.11.021
  • Gargoum, S. A., & El-Basyouny, K. (2016). Exploring the association between speed and safety: A path analysis approach. Accident Analysis & Prevention, 93, 32–40. doi: 10.1016/j.aap.2016.04.029
  • Gomes, S. V., Geedipally, S. R., & Lord, D. (2012). Estimating the safety performance of urban intersections in Lisbon, Portugal. Safety Science, 50(9), 1732–1739. doi: 10.1016/j.ssci.2012.03.022
  • Greibe, P. (2003). Accident prediction models for urban roads. Accident Analysis & Prevention, 35(2), 273–285. doi: 10.1016/S0001-4575(02)00005-2
  • Gross, F., & Hamidi, A. (2011). Investigation of existing and alternative methods for combining multiple CMFs (Report No. T, 06-013). FHWA.
  • Gross, F., Persaud, B., & Lyon, C. (2010). A guide to developing quality crash modification factors (Report No. FHWA-SA-10-032). Washington, DC.
  • Hanley, K., Gibby, A., & Ferrara, T. (2000). Analysis of accident-reduction factors on California state highways. Transportation Research Record, 1717, 37–45. doi: 10.3141/1717-06
  • Hauer, E. (2013). Even perfect regressions may not tell the effect of interventions. Washington, DC. Transportation Research Board 92nd Annual Meeting.
  • Hauer, E., Harwood, D., Council, F., & Griffith, M. (2002). Estimating safety by the empirical Bayes method: A tutorial. Transportation Research Record, 1784, 126–131. doi: 10.3141/1784-16
  • Hauer, E., Kononov, J., Allery, B., & Griffith, M. (2002). Screening the road network for sites with promise. Transportation Research Record, 1784, 27–32. doi: 10.3141/1784-04
  • Heydari, S., Miranda-Moreno, L., & Amador, L. (2013). Does prior specification matter in hotspot identification and before-after road safety studies? Transportation Research Record: Journal of the Transportation Research Board, 2392, 31–39. doi: 10.3141/2392-04
  • Huang, H., Chin, H., & Haque, M. (2009). Empirical evaluation of alternative approaches in identifying crash hot spots: Naive ranking, empirical Bayes, and full Bayes methods. Transportation Research Record, 2103, 32–41. doi: 10.3141/2103-05
  • IBM Corp. (2015). IBM SPSS statistics for windows (version 23). Armonk, NY: IBM Corp.
  • Khan, M., Abdel-Rahim, A., & Williams, C. J. (2015). Potential crash reduction benefits of shoulder rumble strips in two-lane rural highways. Accident Analysis & Prevention, 75, 35–42. doi: 10.1016/j.aap.2014.11.007
  • Kim, D.-G., & Lee, Y. (2013). Modelling crash frequencies at signalized intersections with a truncated count data model. International Journal of Urban Sciences, 17(1), 85–94. doi: 10.1080/12265934.2013.774702
  • Kim, D.-G., Washington, S., & Oh, J. (2006). Modeling crash types: New insights into the effects of covariates on crashes at rural intersections. Journal of Transportation Engineering, 132(4), 282–292. doi: 10.1061/(ASCE)0733-947X(2006)132:4(282)
  • Lan, B., Persaud, B., Lyon, C., & Bhim, R. (2009). Validation of a full Bayes methodology for observational before–after road safety studies and application to evaluation of rural signal conversions. Accident Analysis & Prevention, 41(3), 574–580. doi: 10.1016/j.aap.2009.02.010
  • Lee, C., Abdel-Aty, M., Park, J., & Wang, J.-H. (2015). Development of crash modification factors for changing lane width on roadway segments using generalized nonlinear models. Accident Analysis & Prevention, 76, 83–91. doi: 10.1016/j.aap.2015.01.007
  • Li, X., Lord, D., & Zhang, Y. (2010). Development of accident modification factors for rural frontage road segments in Texas using generalized additive models. Journal of Transportation Engineering, 137(1), 74–83. doi: 10.1061/(ASCE)TE.1943-5436.0000202
  • Lord, D., & Bonneson, J. (2007). Development of accident modification factors for rural frontage road segments in Texas. Transportation Research Record, 2023, 20–27. doi: 10.3141/2023-03
  • Lord, D., & Mannering, F. (2010). The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives. Transportation Research Part A: Policy and Practice, 44(5), 291–305.
  • Maina, E. (2009). Developing crash modification factors for operational parameters on urban freeway. Newark, NJ: New Jersey Institute of Technology.
  • NCHRP. (2008). Crash reduction factors for traffic engineering and ITS improvements (Report No. Final Report Project 17-25). Washington, DC.
  • Oh, J., & Park, D. (2014). Analysis on crash reduction factors for road segment safety. International Journal of Urban Sciences, 18(3), 396–403. doi: 10.1080/12265934.2014.955124
  • Park, J., & Abdel-Aty, M. (2016). Evaluation of safety effectiveness of multiple cross sectional features on urban arterials. Accident Analysis & Prevention, 92, 245–255. doi: 10.1016/j.aap.2016.04.017
  • Park, J., Abdel-Aty, M., & Lee, C. (2014). Exploration and comparison of crash modification factors for multiple treatments on rural multilane roadways. Accident Analysis & Prevention, 70, 167–177. doi: 10.1016/j.aap.2014.03.016
  • Park, J., Abdel-Aty, M., Wang, J.-H., & Lee, C. (2015). Assessment of safety effects for widening urban roadways in developing crash modification functions using nonlinearizing link functions. Accident Analysis & Prevention, 79, 80–87. doi: 10.1016/j.aap.2015.03.025
  • Pearson, K. (1934). On a new method of determining goodness of fit. Biometrika, 26(4), 425–442.
  • Persaud, B., Lan, B., Lyon, C., & Bhim, R. (2010). Comparison of empirical Bayes and full Bayes approaches for before–after road safety evaluations. Accident Analysis & Prevention, 42(1), 38–43. doi: 10.1016/j.aap.2009.06.028
  • Pitale, J. T., Shankwitz, C., Preston, H., & Barry, M. (2009). Benefit: Cost analysis of in-vehicle technologies and infrastructure modifications as a means to prevent crashes along curves and shoulders (Report No. MN/RC 2009-39). Minneapolis.
  • Queensland Government. (2016). Crash data from Queensland roads. Retrieved from https://data.qld.gov.au/dataset/crash-data-from-queensland-roads
  • Sacchi, E., Sayed, T., & El-Basyouny, K. (2014). Collision modification functions: Incorporating changes over time. Accident Analysis & Prevention, 70, 46–54. doi: 10.1016/j.aap.2014.03.003
  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. doi: 10.1214/aos/1176344136
  • Tegge, R. A., Jo, J.-H., & Ouyang, Y. (2010). Development and application of safety performance functions for Illinois (Report No. FHWA-ICT-10-066).
  • Turner, B. (2011). Estimating the safety benefits when using multiple road engineering treatments. A. R. R. Board. Retrieved from Road Safety Risk Reporter, 11.
  • Turner, S., Singh, R., & Nates, G. (2012). The next generation of rural road crash prediction models: Final report.
  • Wang, J.-H., Abdel-Aty, M., & Wang, L. (2017). Examination of the reliability of the crash modification factors using empirical Bayes method with resampling technique. Accident Analysis & Prevention, 104, 96–105. doi: 10.1016/j.aap.2017.04.022
  • Washington, S. P., Persaud, B. N., Lyon, C., & Oh, J. (2005). Validation of accident models for intersections (Report No. FHWA-RD-03-037). Washington, DC.
  • WHO. (2015). Global status report on road safety 2015. Retrieved from http://www.who.int/violence_injury_prevention/road_safety_status/2015/en/
  • Wood, J. S., Donnell, E. T., & Porter, R. J. (2015). Comparison of safety effect estimates obtained from empirical Bayes before–after study, propensity scores-potential outcomes framework, and regression model with cross-sectional data. Accident Analysis & Prevention, 75, 144–154. doi: 10.1016/j.aap.2014.11.019
  • Wu, L., & Lord, D. (2016). Investigating the influence of dependence between variables on crash modification factors developed using regression models. Transportation Research Board 95th Annual Meeting, TRB, Washington, DC.
  • Young, J., & Park, P. Y. (2013). Benefits of small municipalities using jurisdiction-specific safety performance functions rather than the highway safety manual’s calibrated or uncalibrated safety performance functions. Canadian Journal of Civil Engineering, 40(6), 517–527. doi: 10.1139/cjce-2012-0501
  • Yu, R., Quddus, M., Wang, X., & Yang, K. (2018). Impact of data aggregation approaches on the relationships between operating speed and traffic safety. Accident Analysis & Prevention, 120, 304–310. doi: 10.1016/j.aap.2018.06.007

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