Modeling a Road Safety Composite Index for Two-Way Two-Lane Roads Influenced by Abutting Land Uses

Document Type : Research Paper

Authors

1 MSc. Grad., Department of Civil Engineering, Imam Khomeini International University, Qazvin, Iran

2 Assistant Professor, Department of Civil Engineering, , Imam Khomeini International University, Qazvin, Iran

Abstract

Most crash prediction models in two-way two-lane roads describe the geometric characteristics. This study measures the role of abutting land uses in declining the road safety conditions. The objectives of this study are: (1) Developing a composite index that explains the road safety condition in the road segments running through various land uses; (2) Identifying the land use related roadside hazards that influence the road safety; (3) Determining the share of each land use related factor; and (4) Developing applied methods to enhance roadside safety abutted by land uses. In this study, 74 kilometers of Karaj-Chaloos Road were analyzed using the Data Envelopment Analysis. This method was used to define the resulted efficiency score as a composite index which can best define the safety status in terms of quantitative and qualitative measures. In each segment, the land uses were analyzed in terms of three criteria including the land use density, driveway density, and the roadside hazards utilizing the existing plans and field studies. The measures of these criteria were considered as the imput values of the DEA model. The outputs in the Data Envelopment Analysis model were inversed values of expected crash frequencies which were estimated by compounding the predicted and observed crash frequencies through the Empirical Bayesian methodology. The results by the Data Envelopment Analysis show that the roadside hazards due to abutting land uses would strongly affect the safety indx after which the driveway density and land use density would stand as the second and third factors respectively.

Keywords

Main Subjects


-  AASHTO (2002) ”Roadside Design Guide."Washington: American Association of State Highway and Transportation Officials.
-  Ackaah, W. and Salifu, M. (2011) “Crash prediction model for two-lane rural highways in the Ashanti region of Ghana”, IATSS research, Vol. 35, No.1, pp.34-40.
-  Behnood, H. R., Ayati, E., Hermans, E. and Neghab, M. P. (2014) “Road safety performance evaluation and policy making by data envelopment analysis: A case study of provincial data in Iran”, Scientia Iranica. Transaction A, Civil Engineering, Vol. 21, No. 5, pp.1515-1528.
-  Brthod, C. (2016) “Land use planning measures promoting road safety”, in tac 2016: efficient transportation-managing the demand” -2016 Conference and Exhibition of the Transportation Association of Canada.
-  Cafiso, S., La Cava, G. and Montella, A. (2007) “Safety evaluation process for two-lane rural highways”, Transportation Research Record, Vol. 2019, pp. 136-145.
-  Charnes, A., Cooper, W.W. and Rhodes, E. (1979) “Measuring the efficiency of decision-making units”, European Journal of Opertional Research, Vol. 3, No. 4, pp. 339-338.
-  Hermans, E., Van den Bossche, F. and Wets, G. (2008) “Combining road safety information in a performance index”, Accident Analysis & Prevention, Vol. 40, No. 4, pp. 1337-1344.
-  Hermans, E., Brijs, T., Wets, G. and Vanhoof, K. (2009) “Benchmarking road safety: lessons to learn from a data envelopment analysis”, Accident Analysis & Prevention, Vol. 41, No. 1, pp. 174-182.
-  Ismail, N. and Zamani, H. (2013) “Estimation of claim count data using negative binomial, generalized Poisson, zero-inflated negative binomial and zero-inflated generalized Poisson regression models”, In Casualty Actuarial Society E-Forum, Vol. 41, No. 20, pp. 1-28.
-  Legal Medicine Organization ( 2010) “ Statistical Yearbook”, S.l.
-  Lord, D., Park, B. J. and Model, P. G. (2012) “Negative binomial regression models and estimation methods”, Probability Density and Likelihood Functions, pp.1-15.
-  Mehregan, M. (2006) “Quantitative Models in organizational performance evaluation (data envelopment analysis)”, Second Edition ed. University of Tehran: Faculty of Management Publications.
-  National Research Council (US) (2010) . “Transportation Research Board. Task Force on Development of the Highway Safety Manual and Transportation Officials. Joint Task Force on the Highway Safety Manual, (2010) “Highway Safety Manual” (Vol. 1). AASHTO.
-  Shen, Y., Hermans, E., Ruan, D., Vanhoof, K., Brijs, T. and Wets, G. (2010a) “A DEA-based Malmquist productivity index approach in assessing road safety performance”, In Computational Intelligence: Foundations and Applications, pp. 923-928.
-  Shen, Y., Hermans, E., Ruan, D., Vanhoof, K., Brijs, T. and Wets, G. (2010b) “A DEA-based Malmquist productivity index approach in assessing road safety performance”, In Computational Intelligence: Foundations and Applications, pp. 923-928.
-  Shen, Y., Hermans, E., Brijs, T., Wets, G. and Vanhoof, K. (2012) “Road safety risk evaluation and target setting using data envelopment analysis and its extensions”, Accident Analysis & Prevention, Vol. 48, pp. 430-441.
-  Songpatanasilp, P., Yamada, H., Horanont, T. and Shibasaki, R. (2015) “Traffic  accidents risk analysis based on road and land use factors using GLMs and zero-inflated models”, In Proceedings of 14th International Conference on Computers in Urban Planning and Urban Management (CUPUM 2015), pp. 7-10.
-  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), pp.18-29.
-  World Health Organization (2015) “Global status report on road safety 2015”, World Health Organization.