**2. Background**

When examining the number of road mishaps as a meaning of a given country's economic level, Xu *et al*. [13] concluded that "road users' income is a determining factor for road safety." Concurring to its 2013 Global Status Report on road safety, such a conclusion is also reached by the World Health Organization, as low- and middleincome countries show higher traffic death rates when associated with high-income economies. Additional authors also report this cause–effect relationship [12, 14–16]. Overall, these authors claim that a low per capita income is a decisive factor for traffic crashes.

These accidents affect different social areas, and for this reason the subject of road education is a responsibility that belongs to a whole society, which encompasses pedestrians, cyclists, motorcyclists, drivers of vehicles, passengers, and transportation. Improving road education involves an analysis of human behavior, where both classroom instruction on safety issues, laws and regulations, vehicle operation, and those factors affecting driving, as well as vehicle driving practice are combined with a trained instructor [3]. It is for these reasons that the vast majority of road education exams have focused on accidents [4].

*Probability to Be Involved in a Road Accident: Transport User Socioeconomic Approach DOI: http://dx.doi.org/10.5772/intechopen.106325*

Regarding age, on the other hand, much of the road safety literature focuses on high-risk drivers, often being young, low-income men with low education [17]. It is recognized that older people appear to be more safety-conscious [18].

In terms of income, it should be noted that per capita income has been identified as a determinant of overall injury mortality [19]. Based on research conducted by Zmud and Arce [20, 21], it is ensured that lower-middle income groups may be at increased risk of occupant motor vehicle injuries. Attitude is a very important factor in road education, which also predicts longitudinally an unsafe driver [22].

### **2.1 Multi-criteria models for the decision-making process**

For this process, three decision-making models are discussed that are based on the manipulation of the simple related data that provide the means to develop indicators in a systematic way [23]. These decision-making criteria represent a multi-criteria approach, which must be compared with other processes of several criteria such as the qualification model, the hierarchical analytical process (AHP), and the multiple attribute utility theory. The AHP method is a method that has been applied to deal with problems in different areas, matching the sentences of intangible qualitative criteria with tangible quantitative criteria [24]. The AHP method was initially developed by Saaty [25], with the objective of determining the relative importance of a set of alternatives in a multi-criteria decision problem. There are three main steps in the AHP: design of the hierarchy, a prioritization procedure, and the calculation of the results.
