## 2 Risk Factors and Risk Management Methods at Level Crossings  
The identification of the parameters that influence the LC risk has been one of the greatest challenges in recent years. The goal was to identify these parameters, mainly related to traffic conditions (road and rail), environmental conditions, technical factors, and human-caused factors [2], and to correlate them to the frequency and the accidental consequences for the prediction of present risk levels and predicting future ones [3]. Different types of models have been proposed over the years, and, in particular, those based on statistical approaches, such as safety performance factors (SPFs), have generally returned the highest precision and objectivity [1]. This type of model is based on mathematical equations that relate the accident frequency with a series of risk factors and regression factors derived from the statistical analysis of accident data series. Some of the main key risk factors for LCs that the models proposed in the literature have taken into account are summarized in Table 1 (the risk factors considered in each study are traced with \"X\") and refer to the railway and road operational characteristics, the geometry and quality of the road [4], the characteristics of the railway and the type of signaling and external factors. As shown, crucial risk factors identified in the literature are mainly the amount of vehicles and trains that interact at an LC, the train speed, and how the LC is protected. Information like road width, sight distance, car driver (age, gender), and environmental conditions also seem to be chosen to assess the final risk level of LCs. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline  & [5] & [6] & [7] & [8] & [9] & [1] & [10] & [11] & [12] & [13] & [14] & [15] & [2] & [16] \\ \hline AADT road & X & X & X & X & X & X & X & & & & & X \\ \hline AADT train & X & X & X & & & X & X & X & X & & & X \\ \hline Train speed & X & & & X & X & & X & X & & X & & X \\ \hline Road vehicle speed & & & & X & & X & X & & & & X & \\ \hline HV \% & & & & & & & X & & & & \\ \hline Number of tracks & & & X & & & & & X & & & & \\ \hline Road width & X & X & & & & & & & X & & X \\ \hline Road pavement & & & & X & X & & & & & & X & \\ \hline Railway slope & & & & & & & & & & & X \\ \hline Vehicle type & & & & & & & & & & & X & X \\ \hline Skew angle & & & & & & & & & & & X & \\ \hline Sight distance & & & X & & X & & & & X & & X & \\ \hline Rail signaling/type of LC & X & X & X & X & X & X & & & & X & \\ \hline Traffic calming & & & & & & & & & & & \\ (speed humps, & & & & & & & & & & \\ horizontal markings) & & & & & & & & & & & \\ \hline Near misses/accident history & & & & & & & & & & & X & \\ \hline Car driver (age, gender) & & & & & & & & & X & X & & X \\ \hline Environmental conditions & X & & & & & & & & X & X & \\ \hline \end{tabular}
\end{table} 
Table 1: Review of factors affecting risk at LCs. These studies, however, despite providing important information on the elements to consider for risk calculation and their role, do not highlight how to integrate the results within a decision-making process to support the management of a railway. In this sense, the Risk Management (RM) process provides an important tool for studying the accident rate of level crossings and for evaluating action strategies for safeguarding safety levels. RM has seen its development in numerous disciplines [17; 18; 19], allowing, through successive steps, for the identification, assessment, and treatment of the risk of a system and, when used in conditions of limited resources, it constitutes a powerful tool for the decision and prioritization of interventions [20]. The use of risk-based analysis frameworks for assessing safety levels in railway systems has been addressed over the years [21]. In the early 2000s, [PERSON] [22] introduced a railway safety risk model that utilized a combination of fault tree analysis (FTA) and event tree analysis (ETA) to provide a structured representation of the causes and consequences of potential accidents.