Measuring road safety advance by IW-EDAS-KNN: A case study for OAS countries

Abstract

Road Safety is an important aspect when considering the public health of a nation. Road Safety is becoming an increasing concern among nations, and road safety hazards remained a huge problem in some nations, causing financial loss and fatalities. Estimated results demonstrates that road traffic injuries cost the government approximately 3% of GDP, and up to 5% in low- and middle-income countries [1]. Since the road traffic incidence created substantial financial burden, it is necessary to control risk factors and improve the road safety advance. By evaluating the road safety conditions of each individual states, or by comparing the road safety status of a group of states, we can identify the potential strengths and weaknesses of each state hence give suggestions for future improvements. This paper looks at a ten-year data (2009-2019), source from the World Health Organization, the Pan American Health Organization, and the Traffic Safety Data and Analysis Group. The aim of this research is to evaluate and benchmark the road safety conditions of the members states of the Organization of American States by applying Evaluation Based on Distance from Average Solution, a Multi-Criteria Decision-Making (MCDM) technique for classification; identify the continuity in development and advancement of road safety conditions for each state; group the member states of OAS into classes by applying K-Nearest Neighbor Analysis, an algorithm for classification and regression that group objects into classes based on its k nearest neighbors; and make suggestion for future improvements for each member states with respect to their group members. It is concluded that certain indicators are underperformed by a majority of OAS members, which allowed policymakers to identify the potential weakness in road safety performance and offer effective intervention. Additionally, suggestions are made for under-performing countries of the OAS to refer to the road safety procedure from the best-performing nations for future road safety advances.

Decision analysis with IDOCRIW-QUALIFLEX approach in the 2TLq-ROF environment: An application of accident prediction models in Pakistan

“… 3 = 0.0643, 1 = 0.0438, 8 = 0.0389, 7 = 0.0408, 6 Safe E-scooter operation alternative prioritization [69] = 0.0352, 2 = 0.0561, 4 = 0.0576, 3 = 0.0628. 5 = 0.0526, 4 = 0.5737, 3 = 0.6266, 2 = 0.8465, 8 Measuring road safety advance for OAS countries [70] = 0.5457, 5 = 0.3037, 7 = 0.4853, 6 = 0.5537. 1 = 5.1128, 1 …”

“…We make a comparison of our proposed approach with existing approaches involving the case studies such as reducing of human risks on the regional road network of Calabria to improve road safety [7] , safe E-scooter operation alternative prioritization [69] , measuring road safety advance for OAS countries [70] , evaluation of the route selection in international freight transportation [71] , and a lesson system of legislation and regulation for the United States [72] . When we compare the proposed approach with reference [7] the ranking is , with reference [69] the ranking is , with reference [70] the ranking is , with reference [71] the ranking is , with reference [72] the ranking is , the best alternatives are , respectively.…”