A safe speed guidance model for highways

References

• Andrade, G. R. D. (2012). Capacidade e relação fluxo-velocidade em autoestradas e rodovias de pista dupla paulistas ( Master's dissertation). Universidade de São Paulo, Brazil. doi:10.11606/D.18.2012.tde-21062012-103018.
   Google Scholar
• Bellagamba, G., & Cariti, G. (2010). Il nuovo codice della strada. Milano: Giuffrè Editore.
   Google Scholar
• Bi, Y., Srinivasan, D., Lu, X., Sun, Z., & Zeng, W. (2014). Type-2 fuzzy multi-intersection traffic signal control with differential evolution optimization. Expert Systems with Applications, 41(16), 7338–7349.
   Web of Science ®Google Scholar
• Boclin, A. S. C., & De Mello R. (2006). A decision support method for environmental impact assessment using a fuzzy logic approach. Ecological Economics, 58.1(1), 170–181.
   Web of Science ®Google Scholar
• Brasil, C. D. T. B. (2007). Código de trânsito brasileiro: Instituído pela Lei n° 9.503. de 23-9-97. 3 ed. Brasília: DENATRAN. http://www.denatran.gov.br/images/CTB/CTB2015.pdf ( accessed 23 September 2016).
   Google Scholar
• Carlson, P. J., Fontaine, M., Hawkins, H. G., Murphy, K., & Brown, D. (2000, January). Evaluation of speed trailers at high-speed temporary work zones. In 79th Annual Meeting of TRB. Washington, DC.
   Google Scholar
• Chai, G., Huang, M. M., Han, J., & Jiang, M. (2015). Matching method for emergency plans of highway traffic based on fuzzy sets and rough sets. Journal of Intelligent & Fuzzy Systems, 29(6), 2421–2427.
   Web of Science ®Google Scholar
• DENATRAN – Departamento Nacional de Trânsito. (1998). Resolução N° 66, de 23 de setembro de 1998. Retrieved from http://www.denatran.gov.br/download/Resolucoes/resolucao066_98.doc ( accessed 23 September 2016).
   Google Scholar
• Diakaki, C., Papageorgiou, M., Papamichail, I., & Nikolos, I. K. (2015). Overview and analysis of vehicle automation and communication systems from a motorway traffic management perspective. Transportation Research Part A: Policy and Practice, 75, 147–165.
   Web of Science ®Google Scholar
• Forbes, G. (2012). Methods and practices for setting speed limits: An informational report (Report No. IR-133).
   Google Scholar
• Hellinga, B., & Mandelzys, M. (2011). Impact of driver compliance on the safety and operational impacts of freeway variable speed limit systems. Journal of Transportation Engineering,137(4), 260–268.
   Google Scholar
• Hoeg, W., & Lauterbach, T. (Eds.). (2009). Digital audio broadcasting: Principles and applications of DAB, DAB+ and DMB. Chichester: John Wiley & Sons.
   Google Scholar
• Hosseinpour, M., Yahaya, A. S., Ghadiri, S. M., & Prasetijo, J. (2013). Application of adaptive neuro-fuzzy inference system for road accident prediction. KSCE Journal of Civil Engineering, 17(7), 1761–1772.
   Web of Science ®Google Scholar
• Jägerbrand, A. K., & Sjöbergh, J. (2016). Effects of weather conditions, light conditions, and road lighting on vehicle speed. Springer Plus, 5(1), 1–17.
   PubMedGoogle Scholar
• Katz, B., O'Donnel, C., Donoughe, K., Atkinson, J., Finley, M., Balke, K., … Warren, D. (2012). Guidelines for the use of variable speed limit systems in wet weather (Report No. FHWA-SA-12-022). US Department of Transportation.
   Google Scholar
• King, T. W., Sun, C. C., & Virkler, M. R. (2004). Evaluation of a freeway work zone advance speed advisory system using multiple measures. Washington, DC: Transportation Research Board 2004 Annual Meeting.
   Google Scholar
• Lee, W.-H., Tseng, S.-S., & Shieh, W.-Y. (2010). Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system. Information Sciences, 180(1), 62–70.
   Web of Science ®Google Scholar
• INFORM GmbH - Manual, FuzzyTech Users. (2000). Germany: Inform Software Corporation.
   Google Scholar
• Massad, E., Ortega, N. R., & Silveira, P. S. (2004). Métodos quantitativos em medicina. Sao Paulo: Editora Manole Ltda.
   Google Scholar
• Niittymäki, J. (2002). Fuzzy traffic signal control: Principles and applications. Espoo: Helsinki University of Technology.
   Google Scholar
• Pérez, J., Milanés, V., Godoy, J., Villagra, J., & Onieva, E. (2013). Cooperative controllers for highways based on human experience. Expert Systems with Applications, 40(4), 1024–1033.
   Web of Science ®Google Scholar
• Placer, J. (2001). Fuzzy variable speed limit device modification and testing, Phase II (No. AZ-466 (2)). Tucson, AZ: Arizona Department of Transportation.
   Google Scholar
• Placer, J., & Sagahyroon, A. (1998). Fuzzy variable speed limit device project (No. FHWA-AZ-98-466). Tucson, AZ: Arizona Department of Transportation.
   Google Scholar
• Shrestha, K. J., & Shrestha, P. P. (2016). Comprehensive framework for speed-zone guidelines. Journal of Traffic and Transportation Engineering (English Edition), 3(4), 352–363.
   Google Scholar
• Veneziano, D., Hayden, L., & Ye, J. (2010). Effective deployment of radar speed signs. Bozeman: Western Transportation Institute.
   Google Scholar
• Wang, P., Liu, F., Li, D., & Van, N. N. (2014). A traffic flow phase adaptive routing for vehicular communication on highways. EURASIP Journal on Wireless Communications and Networking, 2014(1), 1–12.
   Google Scholar
• Weber, L., & Klein, P. A. T. (2003). Aplicacao da logica fuzzy em software e hardware. Canoas: Editora da ULBRA.
   Google Scholar
• Whitmire, J., Morgan, J. F., Oron-Gilad, T., & Hancock, P. A. (2011). The effect of in-vehicle warning systems on speed compliance in work zones. Transportation Research Part F: Traffic Psychology and Behavior, 14(5), 331–340.
   Web of Science ®Google Scholar