Assessment of Exposure Proxies for Macroscopic Road Safety Prediction

Abstract

Road safety is a major global health problem, and no effort should be spared in trying to limit its impacts. Modeling road safety is a complex task that needs to consider both the quantifiable impact of specific parameters and the underlying trends that cannot always be measured or observed. Macroscopic data often are not available or not in the desired form. Therefore, consideration of alternative sources of data is often required; these sources may be correlated with the modeled phenomenon. The objective of this research was to investigate the suitability of alternative proxy variables for macroscopic road safety modeling by using three suitable exposure proxies: number of vehicles in circulation, gross domestic product, and fuel consumption. Several structural time series models were developed for each proxy for two Mediterranean countries with many similar socioeconomic characteristics: Greece and Cyprus. From the findings of this analysis, a number of observations can be drawn. Proxy variables can provide reasonable results when exposure data are not available. Furthermore, even in two countries with many similarities, the selected proxy measure differs. This finding suggests that the underlying conditions that make a variable a suitable proxy for exposure are complex and need further investigation.