**5. Conclusions**

The chapter shows how the statistical *logit* probability model can characterize the effect of socioeconomic and educational factors on the population and the probability of being involved in a traffic accident. The overall result for the population surveyed identify both the level of road education and the income of the users' infrastructure. The significant variables that influence the probability of the user being involved in a traffic accident by transport mode are as follows:

Amongst freight drivers, it was found that the most significant variables influencing the probability of being involved in a road accident are income and years with a driver's license. Vehicle drivers, age (Age), income (Income), if you have a driver's license (DL), and the age at which you gained road knowledge (ARK) were found to be the most significant variables to determine the probability of being in a road accident. It was found that for motorcyclists the factors were the level of road knowledge (LRK) they were considered to have, years of driver's license (YDL) and Courtesy and Urbanity (C&U) as being the most significant variables for these users. For cyclists, it was found that income as well as courtesy and urbanity were the most significant variables. On the other hand, for pedestrians, it was found that the income, age, level of roadway knowledge that they considered to have, the age at which they obtained road knowledge, and the situations applied were the most significant variables.

In the case of motorized means of transport, the following aspects should be considered; age of users, socioeconomic characteristics, age and origin of acquired knowledge, and courtesy and urbanity. In the case of nonmotorized means of transport, the aspects to be taken into account are age, socioeconomic characteristics, age and origin of acquired knowledge, courtesy and urbanity, and the situations applied in this way.

The results of this research can be useful in defining road safety policies. In this sense, Mirzaei et al. [7] suggest that campaigns could be carried out to strengthen educational programs to minimize the probability of road accidents, considering the socioeconomic status and road education aspects of road users.
