Ranking Causes of Road Accident Occurrence Using Extended Interval Type-2 Fuzzy TOPSIS
Over the past century there has been a dramatic increase in the number of road accidents in Malaysia. Hence, it is necessary to create a decision making method which can consider various preferences and criteria in order to identify the main causes of the accidents. This paper proposes an Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method which provides a comprehensive valuation from experts. This method is developed based on the aggregation of experts’ opinions on preferred causes of road accidents. The extended IT2FTOPSIS employs a linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach (from an ambiguity and type-reduction methods) to formulate a collective decision environment. Three authorised personnel from three Malaysian Government agencies were interviewed where they were asked to rank the causes. The analysis shows that the linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach are effective in measuring the uncertainties in the interviewees’ responses. Thus this paper concludes that the extended IT2FTOPSIS is more aligned with the users’ decisions compared to the earlier IT2FTOPSIS.
Keywords: Multiple criteria decision-making; interval type-2 fuzzy set; IT2FTOPSIS; road accidents
Arnett, J. J., Offer, D., & Fine, M. A. (1997). Reckless driving in adolescence: ‘State’ and ‘trait’ factors. In B-A. Orit Taubman, F. Victor, & M. Mario. Does a threat appeal moderate reckless driving? A terror management theory perspective. Journal of Accident Analysis and Prevention, 32, 1–10.
Ban, A., Brândaş, A., Coroianu, L., Negruţiu, C., & Nica, O. (2011). Approximations of fuzzy numbers by trapezoidal fuzzy numbers preserving the ambiguity and value. Computers & Mathematics with Applications, 61(5), 1379-1401.
Baumrind, D. (1987). A developmental perspective on adolescent risk taking in contemporary America. In C. E., Irwin (Ed.), Adolescent social behavior and health (New directions for child development). Social and Behavioral Science Series, vol. 37. San Francisco: Fall, Jersey-Bass.
Bernama. (2006). Fatal road accident. Retrieved from http://www.bernama.com.my/bernama/v3/news. php?id=213066.
Blincoe, K. M., & Jones, A. P. (2006). Speeding drivers’ attitudes and perceptions of speed cameras in rural England. Journal of Accident Analysis and Prevention, 38, 371–378.
Chen, C., 2000. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1–9.
Chen, S-M. & Wang, C-Y. (2013). Fuzzy decision making systems based on interval type-2 fuzzy sets. Information Sciences, 242, 1–21.
Chen, S-M., & Lee, L-W. (2010). Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Journal of Expert Systems with Application, 37, 2790-2798.
Chen, T-Y. (2013). A signed-distance-based approach to importance assessment and multi-criteria group decision analysis based on interval type-2 fuzzy set. Knowledge Information Systems, 35(1), 193–231.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.
Elkind, D. (1978). Understanding the young adolescent. Edolescence, 13, 127–124.
Finn, P., & Bragg, B. (1986). Perception of risk of an accident by younger and older drivers. Accident Analysis and Prevention, 18, 289–298.
Forman, E. (2007). Conflicts in decision making. Retrieved from www.expertchoice.com
Hassan, T. A., & Mohamed, A. A. (2002). Investigating driver injury severity in traffic accidents using fuzzy ARTMAP. Journal of Computer-Aided Civil and Infrastructure Engineering, 17, 398-408.
Hejar, A. R., Kulanthayan, S., Nor Afiah, M. Z., & Law, T. H. (2005). Car occupants accidents and injuries among adolescents in a state in Malaysia. Proceedings of the Eastern Asia Society for Transportation Studies, 5, 1867-1874.
Holland, C. A., & Conner, M. T. (1996). Exceeding the speed limit: an evaluation of the effectiveness of a police intervention. Accident Analysis Prevention, 28(5), 587–597.
Hu, J., Zhang, Y., Chen, X., & Liu, Y. (2013). Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number. Knowledge-Based Systems, 43, 21–29.
Hwang, C. L., & Yoon, K. S. (1981). Multiple attribute decision making: methods and applications. Berlin: Springer-Verlag.
John, R., & Coupland, S. (2012). Type-2 fuzzy logic: challenges and misconceptions. IEEE Computational Intelligence Magazine, 7(3): 48-52.
Jonah, B. (1986). Accident risk and risk-taking behavior among young drivers. Accident Analysis and Prevention, 18, 255–271.
Khosravi, A., Nahavandi, S., & Khosravi, R. (2013). A new neural network-based type reduction algorithm for interval type-2 fuzzy logic systems. IEEE International Conference on Fuzzy Systems, pp. 1-6.
Lee, L.W., & Chen, S.M. (2008). Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets. In Proceedings of the 2008 International conference on machine learning and cybernetic (pp. 3260-3265) Kunming: China.
Lex Service. (1997). Lex Report on Motoring. Driving for Safety. London: Lex Service Plc.
Lopez, L. (2003). Conflict resolution and group decision making: exploring the dynamics of conflict resolution at the group level. Retrieved from http://www.systemdynamics.org/conferences/2004/SDS_2004/PAPERS/361LOPEZ.pdf
Mannix, E. (2003). Editor’s comments: Conflict and conflict resolution – a return to theorizing.
Martin, D. B., Francis, N. T. M., Pamela, P., & Anthony, L. (2007). The patterns of facial injury suffered by patients in road traffic accidents: a case controlled study. International Journal of Surgery, 5, 250-254.
Mendel, J. M. (2007). Advances in type-2 fuzzy sets and systems. Information Sciences, 177 (1), 84–110.
Mendel, J.M., John, R.I., & Liu, F.L. (2006). Interval type-2 fuzzy logical systems made simple. IEEE Transactions on Fuzzy Systems 14(6), 808–821.
Naim, S., & Hagras, H. (2013). A Type 2-Hesitation Fuzzy Logic based Multi-Criteria Group Decision Making System for Intelligent Shared Environments. Journal of Soft Computing, 18, 1305-1319.
Nie, M., & Tan, W. W. (2008). Towards an efficient type-reduction method for interval type-2 fuzzy logic systems. IEEE World Congress on Computational Intelligence, pp. 1425-1432.
Orit Taubman, B-A., Victor, F., & Mario, M. (2000). Does a threat appeal moderate reckless driving? A terror management theory perspective. Journal of Accident Analysis and Prevention, 32, 1–10.
Rothengatter, T. (1991). Automatic policing and information systems for increasing traffic law compliance. Journal Applied Behaviour, 24(1), 85–87.
Royal Malaysian Police. (2008). Statistics of road accident and death. Retrieved from http://www.rmp.gov.my/rmp.
Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. New York: McGraw-Hill.
Sabariah, F. J. (2007). National trauma database May 2006 to April 2007: first report. Kuala Lumpur: National Trauma Database and Clinical Research Centre, Ministry of Health.
Sarkis, M. E-Z. (2004). Road accidents: causes and outcomes. Lebanon: Mednet Liban.
Shedler, J., & Block, J. (1990). Adolescent drug use and psychological health: a longitudinal inquiry. American Psychologist, 45, 612–630.
Triantaphyllou, E., Shu, B., Nieto Sanchez, S. and Ray, T. (1998). Multi-criteria decision making: an operations research approach. Encyclopedia of Electrical and Electronics Engineering, (J.G. Webster, Ed.) (pp. 175-186), NY:John Wiley & Sons.
Wang, J-W., Cheng, C-H., Huang, K-C. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing 9, 377–386.
Wang, W., Liu, X., & Qin, Y. (2012). Multi-attribute group decision making models under interval type-2 fuzzy environment. Knowledge-Based Systems, 30, 121–128.
World Health Organization. (2004). World report on road traffic injuries prevention: summary. Geneva: WHO Press.
Wu, D., & Tan, W. W. (2005). Computationally efficient type-reduction strategies for a type-2 fuzzy logic controller. IEEE International Conference on Fuzzy Systems, pp. 353-358.
Wu, D. (2012). An overview of alternative type-reduction approaches for reducing the computational cost of interval type-2 fuzzy logic controllers. IEEE World Congress on Computational Intelligence, pp. 1-8.
Wu, H., & Mendel, J. M. (2002). Uncertainty Bounds and Their Use in the Design of Interval Type-2 Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems, 10 (5), 622-639.
Zamri, N., Naim, S., & Abdullah, L. (2015). A new linguistic scale for interval type-2 trapezoidal fuzzy number based multiple criteria decision making method, IEEE International Conference on Fuzzy Systems, pp. 1–9.