Combining Traffic Safety Exposure Indicators in a Composite Exposure Index

  • Bojana TODOSIJEVIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
  • Dalibor PEŠIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
  • Boris ANTIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
  • Krsto LIPOVAC University of Belgrade, Faculty of Transport and Traffic Engineering
  • Filip FILIPOVIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
Keywords: exposure, indicators, risk, TOPSIS, PROMETHEE


The problem of choosing only one relevant safety performance indicator for the purpose of comparing and assessing road safety situations has been the subject of many recent research studies. This paper shows the concept of creating a composite exposure index based on available data. The procedure of creating a model for calculating this indicator is based on the analysis of quality of individual exposure indicators and the size of their impact on the direct safety performance indicators – number of road crashes and their consequences. The following four models (TOPSIS EQUAL, TOPSIS CRIT-IC, PROMETHEE EQUAL, PROMETHEE CRITIC) for determining weighted coefficients of the individual indi-cators that participate in the creation of the composite exposure index have been analysed in this paper. The method used for defining the composite exposure index is the “high-efficiency method” based on which the final shape of the model for defining the composite exposure index has been defined. The main aim of this paper is to create a model for defining the composite index of traffic exposure. The final outcome is to provide an opportuni-ty to evaluate and rank traffic safety levels based on the unique road traffic risk.


Wegman F, Oppe S. Benchmarking road safety performances of countries. Saf Sci. 2010;48(9): 1203–11. doi: 10.1016/j.ssci.2010.02.003.

Eksler V. Measuring and understanding road safety performance at local territorial level. Saf Sci. 2010;48(9): 1197–202. doi: 10.1016/j.ssci.2009.12.010.

Hakkert AS, Braimaister L. The uses of exposure and risk in road safety studies. SWOV Institute for Road Safety Research. Report No. R-2002-12, 2002.

Hauer E. On exposure and accident rate. Traffic Eng Control. 1995;36(3): 134–8.

Al Haji G. Road safety development index (RSDI): Theory, philosophy and practice; 2007.

Kukić D, Lipovac K, Pešić D, Vujanić M. Selection of a relevant indicator - Road casualty risk based on final outcomes. Saf Sci. 2013;51(1): 165–77. doi: 10.1016/j.ssci.2012.06.016.

Kukić D, Lipovac K, Pešić D, Rosić M. The differences of road safety performance of countries based on outcome indicators. Saf Sci. 2016;89: 279–87. doi: 10.1016/j.ssci.2016.07.005.

New Zealand. Road safety strategy 2010: A consultation document. Wellington N.Z.: National Road Safety Committee, Land Transport Safety Authority; 2000. 102 p. [cited 13th June 2019].

Wegman F, Lynam D, Nilsson G. SUNflower: A comparative study of the developments of road safety in Sweden, the United Kingdom, and the Netherlands. SWOV, Leidschendam; 2002.

Hermans E, Van den Bossche F, Wets G. Combining road safety information in a performance index. Accid Anal Prev. 2008;40(4): 1337–44. doi: 10.1016/j.aap.2008.02.004.

Wang Y, Bai H, Xiang W. Traffic safety performance assessment and multivariate treatments for intersection locations. Balt J Road Bridg Eng. 2011;6(1): 30–8. [cited 13th June 2019].

Pešić D, Vujanić M, Lipovac K, Antić B. New method for benchmarking traffic safety level for the territory. Transport. 2013;28(1): 69–80. doi: 10.3846/16484142.2013.781539.

Intan Suhana MR, Hamid H, Law TH, Sadullah AFM. Identification of hazardous road sections: Crash data versus composite index method. Int J Eng Technol. 2014;6(6): 481–6. doi: 10.7763/IJET.2014.V6.745.

Shen Y, Hermans E, Brijs T, Wets G. Fuzzy data envelopment analysis in composite indicator construction. In: Emrouznejad A, Tavana M. (eds) Performance Measurement with Fuzzy Data Envelopment Analysis. Studies in Fuzziness and Soft Computing. Vol 309. Springer, Berlin, Heidelberg; 2014. p. 89–100. doi: 10.1007/978-3-642-41372-8_4 [cited 13th June 2019].

Chen F, et al. Benchmarking road safety performance: Identifying a meaningful reference (best-in-class). Accid Anal Prev. 2016;86: 76–89. doi: 10.1016/j.aap.2015.10.018.

Rosić M, et al. Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method. Accid Anal Prev. 2017;98: 277–86. doi: 10.1016/j.aap.2016.10.007.

Tešić M, Hermans E, Lipovac K, Pešić D. Identifying the most significant indicators of the total road safety performance index. Accid Anal Prev. 2018;113(January): 263–78. doi: 10.1016/j.aap.2018.02.003.

Statistical Database - United Nations Economic Commission for Europe. [Accessed 29th Jan. 2021].

OECD Statistics. [Accessed 29th Jan. 2021].

Diakoulaki D, Mavrotas G, Papayannakis L. Determining objective weights in multiple criteria problems: The critic method. Comput Oper Res. 1995;22(7): 763–70. doi: 10.1016/0305-0548(94)00059-H.

Hwang C-L, Yoon K. Methods for Multiple Attribute Decision Making. In: Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems. Vol 186. Springer, Berlin, Heidelberg; 1981. p. 58–191. doi: 10.1007/978-3-642-48318-9_3 [cited 13th June 2019].

Lai Y-J, Liu T-Y, Hwang C-L. TOPSIS for MODM. Theory Methodol Eur J Oper Res. 1994;76(3): 486–500. doi: 10.1016/0377-2217(94)90282-8.

Brans JP, Vincke P. A preference ranking organisation method: The PROMETHEE method for multiple criteria decision-making. Manage Sci. 1985;31(6): 647–56. doi: 10.1287/mnsc.31.6.647.

How to Cite
TODOSIJEVIĆ B, PEŠIĆ D, ANTIĆ B, LIPOVAC K, FILIPOVIĆ F. Combining Traffic Safety Exposure Indicators in a Composite Exposure Index. Promet [Internet]. 2022Mar.31 [cited 2022May28];34(2):211-2. Available from: