Due to the need to update the current guidelines for highway design to focus on safety, this study sought to build an accident prediction model using a Geographic Information System (GIS) for single-lane rural highways, with a minimum of statistically significant variables, adequate to the Brazilian reality, and improve accident prediction for places with similar characteristics. A database was created to associate the accident records with the geometric parameters of the highway and to fill in the gaps left by the absence of geometric highway plans through geometric reconstitution or semi-automatic extraction of highways using satellite images. The Generalized Estimating Equation (GEE) method was applied to estimate the coefficients of the model, assuming negative distribution of the binomial error for the count of observed accidents. The accident frequency and annual average daily traffic (AADT) were analyzed, along with the spatial and geometric characteristics of 215 km of federal single-lane rural highways between 2007 and 2016. The GEE procedure was applied to two models having three variations of distinct homogeneous segmentation, two based on segments and one based on the kernel density estimator. To assess the effect of constant traffic, two more variations of the models using AADT as an offset variable were considered. The predominant correlation structure in the models was the exchangeable. The principal contributing factors for the occurrence of collisions were the radius of the horizontal curve, the grade, segment length, and the AADT. The study produced clear indicators for the design parameters of roadways that influence the safety performance of rural highways.
References
[1]
Radimsky, M., Matuszkova, R. and Budik, O. (2016) Relationship between Horizontal Curves Design and Accident Rate. Jurnal Teknologi, 78, 75-78.
https://doi.org/10.11113/jt.v78.8493
[2]
Departamento Nacional de Infraestrutura de Transportes DNIT (2010) Manual de projeto e práticas operacionais para seguranca nas rodovias. Instituto de Pesquisas Rodoviárias, Rio de Janeiro.
[3]
Findley, D.J., Hummer, J.E., Rasdorf, W., Zegeer, C.V. and Fowler, T.J. (2012) Modeling the Impact of Spatial Relationships on Horizontal Curve Safety. Accident Analysis & Prevention, 45, 296-304. https://doi.org/10.1016/j.aap.2011.07.018
[4]
Strathman, J.G., Dueker, K.J., Zhang, J. and Williams, T. (2001) Analysis of Design Attributes and Crashes on the Oregon Highway System. Publication FHWA-OR- RD-02-01, Federal Highway Administration, U.S. Department of Transportation, Washington DC.
[5]
Lyles, R.L. and Taylor, W. (2006) Communicating Changes in Horizontal Alignment. NCHRP Report 559, Transportation Research Board, National Research Council, Washington DC.
[6]
Charlton, S.G. (2007) The Role of Attention in Horizontal Curves: A Comparison of Advance Warning, Delineation, and Road Marking Treatments. Accident Analysis and Prevention, 39, 873-885. https://doi.org/10.1016/j.aap.2006.12.007
[7]
Mcgee, H.W. and Hanscom, F.R. (2006) Low-Cost Treatments for Horizontal Curve Safety. Publication FHWA-SA-07-002, Federal Highway Administration, U.S. Department of Transportation, Washington DC.
[8]
Elvik, R. (2013) International Transferability of Accident Modification Functions for Horizontal Curves. Accident Analysis & Prevention, 59, 487-496.
https://doi.org/10.1016/j.aap.2013.07.010
[9]
Organisation for Economic Cooperation and Development (OECD/ITF) (2016) Road Safety Annual Report 2016. OECD Publishing, Paris.
[10]
Abdulhafedh, A.A. (2017) Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord G*i Statistic. Open Journal of Civil Engineering, 7, 208-221.
https://doi.org/10.4236/ojce.2017.72013
[11]
Macedo, M.R.O.B.C., Maia, M.L.A., Kohlman Rabbani, E.R. and Lima Neto, O.C.C. (2020) Remote Sensing Applied to the Extraction of Road Geometric Features Based on OPF Classifiers, Northeastern Brazil. Journal of Geographic Information System, 12, 15-44. https://doi.org/10.4236/jgis.2020.121002
[12]
Ye, X., Pendyala, R., Shankar, V. and Konduri, K. (2013) A Simultaneous Model of Crash Frequency by Severity Level for Freeway Sections. Accident Analysis and Prevention, 57, 140-149. https://doi.org/10.1016/j.aap.2013.03.025
[13]
Yu, R. and Abdel-Aty, M. (2013) Multi-Level Bayesian Analysis for Single- and Multi-Vehicle Freeway Crashes. Accident Analysis and Prevention, 58, 97-105.
https://doi.org/10.1016/j.aap.2013.04.025
[14]
Castro, M., Paleti, R. and Bhat, C.R. (2012) A Latent Variable Representation of Count Data Models to Accommodate Spatial and Temporal Dependence: Application to Predicting Crash Frequency at Intersections. Transportation Research Part B, 46, 253-272. https://doi.org/10.1016/j.trb.2011.09.007
[15]
Park, E.-S., Carlson, P., Porter, R. and Anderson, C. (2012) Safety Effects of Wider Edge Lines on Rural, Two-Lane Highways. Accident Analysis and Prevention, 48, 317-325. https://doi.org/10.1016/j.aap.2012.01.028
[16]
Zegeer, C.V., Stewart, J.R., Council, F.M., Reinfurt, D.W. and Hamilton, E. (1991) Cost-Effective Geometric Improvements for Safety Upgrading of Horizontal Curves. Publication FHWA-RD-90-074, Federal Highway Administration, U.S. Department of Transportation, Washington DC.
[17]
Lee, J. and Mannering, F. (2002) Impact of Roadside Features on the Frequency and Severity of Runoff-Roadway Accidents: An Empirical Analysis. Accident Analysis and Prevention, 34, 149-161. https://doi.org/10.1016/S0001-4575(01)00009-4
[18]
Zegeer, C.V. and Deacon, J.A. (1987) Effect of Lane Widht, Shoulder Widht, and Shoulder Type on Highway Safety. In: Relationship between Safety and Key Highway Features: A Synthesis of Prior Research, State of the Art Report 6, Transportation Research Board, Washington DC, 1-21.
[19]
Vogt, A. and Bared, J. (1998) Accident Models for Two-Lane Rural Segments and Intersections. Transportation Research Record: Journal of the Transportation Research Board, 1635, 18-29. https://doi.org/10.3141/1635-03
[20]
Karlaftis, M. and Golias, I. (2002) Effects of Road Geometry and Traffic Volumes on Rural Roadway Accident Rates. Accident Analysis & Prevention, 34, 357-365.
https://doi.org/10.1016/S0001-4575(01)00033-1
[21]
Shankar, V., Mannering, F. and Woodrow, B. (1995) Effect of Roadway Geometrics and Environmental Factors on Rural Freeway Accident Frequencies. Accident Analysis & Prevention, 27, 371-389. https://doi.org/10.1016/0001-4575(94)00078-Z
[22]
Hadi, M.A., Aruldhas, J., Chow, L.F. and Wattleworth, J.A. (1995) Estimating Safety Effects of Cross-Section Design for Various Highway Types Using Negative Binomial Regression. Transportation Research Center, University of Florida, Gainesville.
[23]
Persaud, B., Retting, R. and Lyon, C. (2000) Guidelines for Identification of Hazardous Highway Curves. Transportation Research Record, 1717, 14-18.
https://doi.org/10.3141/1717-03
[24]
Cafiso, S., Di graziano, A., Di Silvestro, G., La Cava, G. and Persaud, B. (2010) Development of Comprehensive Accident Models for Two-Lane Rural Highways Using Exposure, Geometry Consistency and Context Variables. Accident Analysis and Prevention, 34, 357-365.
[25]
Quddus, A.M., Chao, W. and Stephen, G.I. (2010) Road Traffic Congestion and Crash Severity: Econometric Analysis Using Ordered Response Models. Journal of Transportation Engineering, ASCE, 136, 424-435.
https://doi.org/10.1061/(ASCE)TE.1943-5436.0000044
[26]
Chiou, Y., Lan, L.L. and Chen, W. (2010) Contributory Factors to Crash Severity in Taiwan’s Freeways: Genetic Mining Rule Approach. Journal of the Eastern Asia Society for Transportation Studies, 8, 1865-1877.
[27]
Haleem, K., Abdelaty, M. and Mackie, K. (2010) Using a Reliability Process to Reduce Uncertainty in Predicting Crashes at Unsignalized Intersections. Accident Analysis and Prevention, 42, 654-666. https://doi.org/10.1016/j.aap.2009.10.012
[28]
Mustakim, F. and Fujita, M. (2011) Development of Accident Predictive Model for Rural Roadway. World Academy of Science, Engineering and Technology, 58, 126-131.
[29]
Eluru, N. (2013) Evaluating Alternate Discrete Choice Frameworks for Modeling Ordinal Discrete Variables. Accident Analysis and Prevention, 55, 1-11.
https://doi.org/10.1016/j.aap.2013.02.012
[30]
Boodlal, L., Donnell, E.T., Porter, R.J., Garimella, D., Le, T.Q., Croshaw, K., Himes, S., Kulis, P. and Wood, J. (2015) Factors Influencing Operating Speeds and Safety on Rural and Suburban Roads. Report No. FHWA-HRT-15-030, Federal Highway Administration, Office of Safety Research and Development, McLean.
[31]
Costa, J.O., Freitas, E.F., Jacques, M.A.P. and Pereira, P.A.A. (2016) Collision Prediction Models with Longitudinal Data: An Analysis of Contributing Factors in Collision Frequency in Road Segments in Portugal. RS5C-Road Safety on 5 Continents.
[32]
Kiran, B.N., Kumaraswamy, N. and Sashidhar, C. (2017) A Review of Road Crash Prediction Models for Developed Countries. American Journal of Traffic and Transportation Engineering, 2, 10-25.
[33]
Garnaik, M.M. (2014) Effects of Highway Geometric Elements on Accident Modelling. Thesis Master of Technology in Transportation Engineering, Department of Civil Engineering, National Institute of Technology, Rourkela.
[34]
Agbelie, B.R.D.K. (2016) A Comparative Empirical Analysis of Statistical Models for Evaluating Highway Segment Crash Frequency. Journal of Traffic and Transportation Engineering, 3, 374-379. https://doi.org/10.1016/j.jtte.2016.07.001
[35]
Andriola, C.L. (2018) Análise da frequência e severidade de acidentes viários em curvas de rodovias de pista simples: O caso da BR 116. Masters Dissertation, Civil Engineering Graduate Program, Federal University of Rio Grande Do Sul, 201.
[36]
Anastasopoulos, P.C., Shankar, V.N., Haddockc, J.E. and Mannering, F.L. (2012) A Multivariate Tobit Analysis of Highway Accident Injury-Severity Rates. Accident Analysis & Prevention, 45, 110-119. https://doi.org/10.1016/j.aap.2011.11.006
[37]
Chikkakrishna, N.K., Parida, M. and Jain, S.S. (2017) Identifying Safety Factors Associated with Crash Frequency and Severity on Nonurban Four-Lane Highway Stretch in India. Journal of Transportation Safety & Security, 9, 32-30.
https://doi.org/10.1080/19439962.2016.1150927
[38]
Sameen, M.I. and Pradhan, B. (2016) Forecasting Severity of Traffic Accidents Using Road Geometry Extracted from Mobile Laser Scanning Data. The 37th Asian Conference on Remote Sensing (ACRS), Sri Lanka, 17-21 October 2016, 1-6.
[39]
American Association of State and Highway AASHTO (2014) Transportation Officials. Highway Safety Manual, Washington, EUA.
[40]
Liang, K. and Zeger, S.L. (1986) Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73, 13-22. https://doi.org/10.1093/biomet/73.1.13
[41]
Dong, C., Nambisan, S.S., Richards, S.H. and Ma, Z. (2015) Assessment of the Effects of Highway Geometric Design Features on the Frequency of Truck Involved Crashes Using Bivariate Regression. Transportation Research Part A: Policy and Practice, 75, 30-41. https://doi.org/10.1016/j.tra.2015.03.007
[42]
Cruz, P., Echaveguren, T. and González, P. (2017) Estimación del potencial de rollover de vehículos pesados usando principios de confiabilidad. Revista ingeniería de construcción, 32, 5-14. https://doi.org/10.4067/S0718-50732017000100001
[43]
Erdogan, S., Yilmaz, I., Baybura, T. and Gullu, M. (2008) Geographical Information Systems Aided Traffic Accident Analysis System Case Study: City of Afyonkarahisar. Accident Analysis and Prevention, 40, 174-181.
https://doi.org/10.1016/j.aap.2007.05.004
[44]
Souza, B.F. and Silva, J.P. (2017) Análise Espacial dos acidentes de transito em Passos (MG). Ciência et Praxis, 10, 19-27.
[45]
Mendonca, M.F.S., Silva, A.P.S.C. and Castro, C.C.L. (2017) Análise espacial dos acidentes de transito urbano atendidos pelo Servico de Atendimento Móvel de Urgência: Um recorte no espaco e no tempo. Revista Brasileira de Epidemiologia, 20, 727-741. https://doi.org/10.1590/1980-5497201700040014
