A Novel Approach to Evaluate the Road Safety Index: A Case Study in the Roads of East Azerbaijan Province in Iran

Document Type : Research Paper

Authors

1 Department of Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, Iran

2 Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz, Iran

Abstract

Road safety index is an important indicator that has been recently introduced as a useful tool to measure the quality of life in many countries and cities. Road safety index is a complex index and it has at least three main components, including road user behavior, vehicle safety, and road infrastructure effects. Many researchers have selected studying road performance from road safety index perspective due to its feasibility and applicability. To calculate the road safety index, a novel approach was proposed using data envelopment analysis method. In this paper, the selected road safety indicators are classified into two groups, namely the desirable and undesirable indicators. The new approach was applied for a case study in the roads of East Azerbaijan Province in Iran. Inefficient roads were recognized applying the proposed method, and strategies were suggested to improve the efficiency of these roads.

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Main Subjects


Al-Haji, G. (2007). Road safety development index: Theory, philosophy and practice. Doctoral dissertation, Linköping University Electronic Press.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Barnum, D. T., Tandon, S., & McNeil, S. (2008). Comparing the performance of bus routes after adjusting for the environment using data envelopment analysis. Journal of Transportation Engineering, 134(2), 77-85.
Cafiso, S., Cava, G., & Montella, A. (2007). Safety index for evaluation of two-lane rural highways. Journal of the Transportation Research Board, 2019(1), 136-145.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational Research, 2(6), 429-444.
Elvik, R., Vaa, T., Hoye, A., & Sorensen, M. (Eds.). (2009). The handbook of road safety measures. European Journal of Transport Infrastructure Research, Emerald Group Publishing Limited, ISBN: 9781848552500.
Fallah-Fini, S., Triantis, K., Jesus, M., & Seaver, W. L. (2012). Measuring the efficiency of highway maintenance contracting strategies: A bootstrapped non-parametric meta-frontier approach. European journal of operational research, 219(1), 134-145.
Färe, R., & Grosskopf, S. (2004). Modeling undesirable factors in efficiency evaluation: Comment. European Journal of Operational Research, 157(1), 242-245.
Fu, P., Zhan, Z., & Wu, C. (2013). Efficiency analysis of Chinese Road Systems with DEA and order relation analysis method: Externality concerned. Procedia-Social and Behavioral Sciences, 96, 1227-1238.
Georgiadis, G., Politis, I., & Papaioannou, P. (2014). Measuring and improving the efficiency and effectiveness of bus public transport systems. Research in
58 (IJMS) Vol. 12, No. 2, Spring2019
Transportation Economics, 48, 84-91.
Grande, Z., Castillo, E., Mora, E., & Lo, H. K. (2017). Highway and road probabilistic safety assessment based on bayesian network models. Computer‐Aided Civil and Infrastructure Engineering, 32(5), 379-396.
Harwood, D., Bauer, K., Gilmore, D., Souleyrette, R., & Hans, Z. (2010). Validation of U.S. road assessment program star rating protocol: Application to safety management of U.S. roads. Journal of the Transportation Research Board, 2147(1), 33-41.
Hauer, E. (1997). Observational before/after studies in road safety: Estimating the effect of highway and traffic engineering measures on road safety, Elsevier Science Ltd., Oxford.
Hermans, E., Van den Bossche, F., & Wets, G. (2008). Combining road safety information in a performance index. Accident Analysis & Prevention, 40(4), 1337-1344.
Hermans, E., Van den Bossche, F., & Wets, G. (2009). Uncertainty assessment of the road safety index. Reliability Engineering & System Safety, 94(7), 1220-1228.
Holmgren, J. (2013). The efficiency of public transport operations–An evaluation using stochastic frontier analysis. Research in Transportation Economics, 39(1), 50-57.
Korhonen, P. J., & Luptacik, M. (2004). Eco-efficiency analysis of power plants: An extension of data envelopment analysis. European journal of operational research, 154(2), 437-446.
Li, T., Yang, W., Zhang, H., & Cao, X. (2016). Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China. Transport Policy, 45, 66-76.
Liu, W. B., Meng, W., Li, X. X., & Zhang, D. Q. (2010). DEA models with undesirable inputs and outputs. Annals of Operations Research, 173(1), 177-194.
Mbakwe, A. C., Saka, A. A., Choi, K., & Lee, Y. J. (2016). Alternative method of highway traffic safety analysis for developing countries using Delphi technique and Bayesian network. Accident Analysis & Prevention, 93, 135-146.
Nakanishi, Y. J., & Falcocchio, J. C. (2004). Performance assessment of intelligent transportation systems using data envelopment analysis. Research in Transportation Economics, 8, 181-197.
Odeck, J. (2006). Identifying traffic safety best practice: An application of DEA and Malmquist indices. Omega, 34(1), 28-40.
Roháčová, V. (2015). A DEA based approach for optimization of urban public transport system. Central European journal of operations Research, 23(1), 215-233.
Sacchi, E., Persaud, B., & Bassani, M. (2012). Assessing international transferability of highway safety manual crash prediction algorithm and its components. Journal of the Transportation Research Board, 2279(1), 90-98.
Scheel, H. (2001). Undesirable outputs in efficiency valuations. European journal of operational research, 132(2), 400-410.
Schlögl, M., & Stütz, R. (2017). Methodological considerations with data uncertainty in road safety analysis. Accident Analysis & Prevention, In Press, https://doi.org/10.1016/j.aap.2017.02.001.
Seiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European journal of operational research, 142(1), 16-20.
Shen, Y., Hermans, E., Bao, Q., Brijs, T., & Wets, G. (2013). Road safety development in Europe: A decade of changes (2001–2010). Accident Analysis & Prevention, 60, 85-94.
Shen, Y., Hermans, E., Bao, Q., Brijs, T., Wets, G., & Wang, W. (2015). Inter-national
A Novel Approach to Evaluate the Road Safety Index: A Case Study in the Roads … 59
benchmarking of road safety: State of the art. Transportation research part C: Emerging technologies, 50, 37-50.
Shen, Y., Hermans, E., Brijs, T., Wets, G., & Vanhoof, K. (2012). Road safety risk evaluation and target setting using data envelopment analysis and its extensions. Accident Analysis & Prevention, 48, 430-441.
Shen, Y., Hermans, E., Ruan, D., Wets, G., Brijs, T., & Vanhoof, K. (2011). A generalized multiple layer data envelopment analysis model for hierarchical structure assessment: A case study in road safety performance evaluation. Expert systems with applications, 38(12), 15262-15272.
Tatari, O., Egilmez, G., & Kurmapu, D. (2016). Socio-eco-efficiency analysis of highways: A data envelopment analysis. Journal of Civil Engineering and Management, 22(6), 747-757.
Vis, M.A. (2005). State of the art report on road safety performance indicators. Deliverable D3.1 of the EU Integrated Project Safety Net.
World Health Organization. (2015). Global status report on road safety 2015. World Health Organization, Electronic Press. ISBN: 97 8 92 4 156506 6.
Xie, F., Gladhill, K., Dixon, K., & Monsere, C. (2011). Calibration of highway safety manual predictive models for Oregon state highways. Journal of the Transportation Research Board, 2241(1), 19-28.