The objective of this Diploma Thesis is the estimation of the human cost of road accidents based on the “Willingness-to-Pay” (WTP) methodology, and the identification of drivers attitudes towards the probability of getting involved in a road accident, using the “Stated Preference” method. The later analysis was based on the results of a questionnaire-based on-line survey. The selected data concerned the socio-economic background of the drivers and their preferences towards hypothetical scenarios of reduction of the probability of getting involved in a road accident. An ordinal logistic regression model was developed for estimating the annual amount that drivers are willing to invest; and a multinomial logistic regression model for the prediction of the drivers’ intention to reduce the probability of getting involved in a road accident. The aforementioned reduction was applied in ten hypothetical road safety interventions that increased the cost and the duration of the standard trip. The results demonstrate a positive correlation between the number of road accidents that a driver was involved so far and the annual amount that is willing to invest. Additionally, it was found that most of the drivers support the reduction of the probability to get involved in an accident. Lastly, based on the WTP methodology, the road accident fatality human cost was estimated at 1.761 million euros.
|Tags||accident analysis, impact assessment, statistical modelling|