Using Probabilistic Risk Modeling for Cost-Benefit Analysis: Application to Road Safety Measures

This paper presents a modeling approach to investigate the association of the probability of traffic accident with road safety measures. First, the probability of traffic accident is defined as the ratio of the number of accidents to the number of motor vehicles in a region or country during a period of time. To improve road safety, i.e. decreasing the probability of traffic accidents, road safety measures should be implemented. The law of diminishing marginal returns indicates that as the total investment in a single road safety measure increases, the total return on investment (probability of transportation accident) decreases. Regression analysis is employed to build the relationship between effect (probability of traffic accident) and the cost of a single safety measure based on the limited count data. The expected net benefit, which equals benefit minus the cost of safety measure is given by probabilistic risk model, if the net benefit exceeds zero the corresponding safety measure is identified as cost effective.