# A Unified Approach for Risk Assessment of Road Crash Barriers Using Bayesian Statistics
## 4 The Method  
The input data for the solution of this issue was the database of registered traffic safety defects managed by the Czech Roads and Motorways Directorate [40] and at the same time the database of traffic accidents registered by the Czech Police. For a comprehensive monitoring period of five years (2015 to 2019), a total of 10,198 accidents were recorded on the road network in the Czech Republic [41], for which the type of collision was determined by the police from the category of collision into a restraint system. Of this set of crashes, almost 60% (5987 traffic accidents) were identified on the TEN-T road network [42]. Since it is obvious that the crash barrier is designed to be hit by cars in the event of an accident, the risk level of the crash barriers cannot be calculated based only on recorded accidents at the location of identified crash barrier defects. The determination of the risk level is therefore carried out based on the comparison of the results of a mathematical model designed to compare the two following cases: For the first set of data, the type of mathematical model was filtering input data based on the mutual correlation of traffic accidents and recorded defects in the area of crash barriers. In the second case, the model is based on crash barrier accidents where no defect was located in the road safety inspections. Therefore, no other defects that could negatively affect safety in the area could be recorded in the vicinity of these accident events. A total of 5528 deficiencies in crash barriers were identified in six regions of the Czech Republic (approximately half of the area of the Czech Republic). The mutual relationship between the data set of traffic accidents and identified traffic safety defects of crash barriers was located. This resulted in correlated traffic accidents that are influenced by a traffic-safety deficit from the category of restraint systems. The most common type of deficit is \"Short beginning element of the crash barrier\", which was correlated with crash events in 101 cases (Figure 1). The second most common (80 records) is \"Inadequately realized beginning element of the crash barrier\" (for example, the crash barrier does not have the beginning element sufficiently secured in the ground or there is no beginning element) (Figure 2). \"Failure to maintain minimum clear zone behind the crash barrier\" was identified in 76 correlated records (Figure 3). These three categories represent almost 80% of the entire dataset. The remaining restraint system defects are divided into a further eight categories, but their frequency is negligible and cannot be used for further mathematical evaluation due to the small number of correlated records. In order to determine the theoretical risk for specific road restraint system defects, it is necessary to define the characteristic features of the adjacent road and the parameters of the crash barrier. The assignment of the parameters then generates the individual combinations that the correlated record can acquire. For these combinations, the mathematical model verifies the resulting riskiness of the recorded defect and is able to verify or disprove the hypothesis. Traffic safety defects, for which parameters are defined, have various effects on traffic accidents. Therefore, the selected parameters are not identical for all defects, but may vary. (Table 1) The basic properties of the crash barrier and its immediate surroundings that are monitored are:  
Figure 1: Short turned down end of the crash barrier. Figure 3: Insufficient minimum distance behind the crash barrier. Figure 2: Incorrect beginning/end of the crash barrier. Each of the deficits contains a different number of assigned parameters depending on their specific properties.