Usage of Non-Linear Regression for Modeling the Behavior of Motor Vehicle Crash Fatality (MVF) Rate

Abstract

Data analysis for vehicular crash counts is essential for transportation and traffic management systems (TTMS) to develop practical and innovative road safety interventions. The crash trend analysis, in particular, is the most popular technique for extracting an underlying trend or pattern of behavior in crash data. The recent years have seen a growing concern in the State of Qatar of the consequences of motor vehicle crashes (MVCs) and their associated fatalities (MVFs) on the economy, society, and the performance of the whole road network. This paper reports on the results of using nonlinear regression for crash trend analysis highlighting the substantial enhancement of road safety level in the State of Qatar during the period between 2003 and 2015. One of the critical findings of the study is the notable decline in the increasing tendency of both the MVF/100,000 population and the MVF/100,000 car over the last thirteen years in the State of Qatar. The matter that makes this finding worthy of comment is that it occurs over the period in which the State of Qatar is witnessing a significant growth in the population density and traffic volume. Several valuable contributions and recommendations were drawn and reported. � IEOM Society International.