Incorporating safety into targeted pavement friction data collection and maintenance procedures

References

• Anselin, L. 1995. Local indicators of spatial association – LISA, Geographical Analysis 27(2): 93–115. http://doi.org/10.1111/j.1538-4632.1995.tb00338.x
   Web of Science ®Google Scholar
• ASTM C535-12. Standard Test Method for Resistance to Degradation of Large-Size Coarse Aggregate by Abrasion and Impact in the Los Angeles Machine.
   Google Scholar
• ASTM E274. Standard Test Method for Skid Resistance of Paved Surfaces Using a Full-Scale Tire.
   Google Scholar
• ASTM E501. Standard Specification for Standard Tire For Pavement Skid-Resistance Tests.
   Google Scholar
• De Luca, M.; Dell’Acqua, G.; Lamberti, R. 2012. Road safety analysis using operating speeds: case studies in Southern Italy, Procedia – Social and Behavioral Sciences 53: 702–710. http://doi.org/10.1016/j.sbspro.2012.09.920
   Google Scholar
• De Luca, M; Dell’Acqua, G. 2014. Runway surface friction characteristics assessment for Lamezia Terme airfield pavement management system, Journal of Air Transport Management 34: 1–5. http://doi.org/10.1016/j.jairtraman.2013.06.015
   Web of Science ®Google Scholar
• Dell’Acqua, G.; De Luca, M.; Lamberti, R. 2011. Indirect skid resistance measurement for porous asphalt pavement management, Transportation Research Record: Journal of the Transportation Research Board 2205: 147–154. http://doi.org/10.3141/2205-19
   Web of Science ®Google Scholar
• Dell’Acqua, G.; De Luca, M.; Mauro, R.; Russo, F. 2012. Free-way crashes in wet weather: the comparative influence of porous and conventional asphalt surfacing, Procedia – Social and Behavioral Sciences 54: 618–627. http://doi.org/10.1016/j.sbspro.2012.09.779
   Google Scholar
• DoT. 2015a. Road Weather Management: How Do Weather Events Impact Roads? Federal Highway Administration, US Department of Transportation (DoT). Available from Internet: http://www.ops.fhwa.dot.gov/weather/q1_road-impact.htm
   Google Scholar
• DoT. 2015b. Toward Zero Deaths: A National Strategy on Highway Safety. 2015. Federal Highway Administration, US Department of Transportation (DoT). Available from Internet: http://safety.fhwa.dot.gov/tzd
   Google Scholar
• DoT. 2012a. MAP-21 – Moving Ahead for Progress in the 21st Century. Federal Highway Administration, US Department of Transportation (DoT). Available from Internet: http://www.fhwa.dot.gov/map21/factsheets/hsip.cfm
   Google Scholar
• DoT. 2012b. Traffic Safety Facts 2012: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System. DOT HS 812 032. National Highway Traffic Safety Administration, US Department of Transportation (DoT). 248 p. Available from Internet: http://www-nrd.nhtsa.dot.gov/Pubs/812032.pdf
   Google Scholar
• Getis, A.; Ord, J. K. 1992. The analysis of spatial association by use of distance statistics, Geographical Analysis 24(3): 189–206. http://doi.org/10.1111/j.1538-4632.1992.tb00261.x
   Web of Science ®Google Scholar
• Gokhale, S. V.; Bischoff, D. 2012. Statewide Pavement Friction Testing 2012. Report No WI-06-12. Wisconsin Department of Transportation, Madison, WI. 46 p. Available from Internet: http://wisconsindot.gov/documents2/research/BTS-WI-06-12-final-report.pdf
   Google Scholar
• Loh, W.-Y. 2011. Classification and regression trees, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1(1): 14–23. http://doi.org/10.1002/widm.8
   Web of Science ®Google Scholar
• Loh, W.-Y. 2002. Regression trees with unbiased variable selection and interaction detection, Statistica Sinica 12(2): 361–386.
   Web of Science ®Google Scholar
• Long, K.; Wu, H.; Zhang, Z.; Murphy, M. 2014. Quantitative Relationship between Crash Risks and Pavement Skid Resistance. Report No FHWA/TX-13/0-6713-1. Texas Department of Transportation, Austin, TX. 71 p. Available from Internet: http://library.ctr.utexas.edu/ctr-publications/0-6713-1.pdf
   Google Scholar
• McGovern, C.; Rusch, P.; Noyce, D. A. 2011. State Practices to Reduce Wet Weather Skidding Crashes. Publication FHWA-SA-11-21. Federal Highway Administration, US Department of Transportation. 43 p. Available from Internet: http://safety.fhwa.dot.gov/speedmgt/ref_mats/fhwasa1121/fhwasa1121.pdf
   Google Scholar
• Noyce, D. A.; Bahia, H. U.; Yambo, J.; Chapman, J.; Bill, A. 2007. Incorporating Road Safety into Pavement Management: Maximizing Surface Friction for Road Safety Improvements. Report No. MRUTC 04-04. Wisconsin Department of Transportation, Madison, WI. 241 p. Available from Internet: http://www.wistrans.org/mrutc/files/04-04_MRUTC_FR.pdf
   Google Scholar
• Ord, J. K.; Getis, A. 1995. Local spatial autocorrelation statistics: distributional issues and an application, Geographical Analysis 27(4): 286–306. http://doi.org/10.1111/j.1538-4632.1995.tb00912.x
   Web of Science ®Google Scholar
• Qin, X.; Khan, G.; Noyce, D. A. 2007. Spatial statistical approach to identifying snow crash-prone locations, in TRB 86th Annual Meeting Compendium of Papers CD-ROM, 21–25 January 2007, Washington, DC. 1–20.
   Google Scholar
• Vadakpat, G. C. 1994. Analytical Study of Surface Friction of Wisconsin Trunk Highway System Pavements: MSc Thesis. University of Wisconsin–Madison, Madison, WI. 146 p.
   Google Scholar