# Determining the Safety Level of State Roads: An Italian Case Study
## 5 Case Study
### Safety Indicator Evaluation
#### 5.4.3 Safety Performance Indicators
The safety indicators presented above are calculated for the elementary sections under study. The results are summarized in Table 8. As mentioned above, the adoption of a single safety indicator may not be sufficient to assess the actual safety condition. However, the combination of different indicators allows for a more complete description of the site conditions. For each safety performance indicator, the specific distribution of the total number of elementary sections considered (132 km) falling in each range can be represented by the frequency distribution. Figure 5a shows the distribution of safety rankings by crash frequency. When comparing the observed and expected crash frequencies, the expected one has a more gradual trend with respect to the observed one. For high values of crash frequency, sites have more critical conditions, while for lower values, the safety level increases. In fact, a few 1 km elementary sections have extremely high values of crash frequency and will be the first ones to be inspected. For less critical values of crash frequency, the corresponding number of sections increases, but the inspection is less urgent. A similar reasoning could be conducted for the crash rate according to the results in Figure 5b. The most critical elementary sections are those corresponding to higher values of crash rate. Note that elementary sections characterized by a high crash frequency are not necessarily characterized by a high crash rate. For this reason, it is crucial to evaluate different safety indicators simultaneously to select for further inspection all those sections that may present safety problems in terms of different indicators. Figure 5: Safety performance indicator distribution for 1 km elementary sections according to: (**a**) Crash frequency for observed and expected crashes; (**b**) Crash rate for observed and expected crashes. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{\ \begin{tabular}{c} **Elementary** \\ **Sections (1 km)** \\ \end{tabular}  } & \begin{tabular}{c} **Observed** \\ **Crash** \\ **Frequency** \\ \end{tabular}  & \multirow{2}{*}{**SAPO**} & \multirow{2}{*}{**Exposed**} & \multirow{2}{*}{**Expected**} & \multirow{2}{*}{**Excess of Expected**} \\  & & & & & **Crash Rate** \\ \cline{1-1} \cline{6-6}  & **[Crashes/Year/km]** & & & & **[Crashes/Year/km]** \\ \cline{1-1} \cline{6-6}  & **[Crashes/Year/km]** & & **[**\& **[**\& **\&  
An additional safety indicator based on the HSM method is the excess of expected crashes over predicted crashes. Therefore, a safety ranking is performed for this indicator, and the results are shown in Figure 6a. The most critical safety condition is associated with high and positive values of the excess of crashes. Specifically, 60 sites exhibit a positive value for the excess of crashes. Sites with an excess of crashes value of zero (37 sites) have a safety level equivalent to the average of sites with similar characteristics. In fact, elementary sections commonly fall into this category of zero excess of crashes. Sections with an excess of crashes greater than zero indicate specific site conditions worse than the average, suggesting that the elementary sections should be monitored. On the contrary, sections with an excess of crashes less than zero generally have safer conditions than the average of similar sites, implying fewer urgent inspection needs. SAPO is also considered to express the potential economic benefit of crash reduction. Increasing positive values of SAPO are associated with critical safety conditions because the potential safety benefit is greater. Decreasing negative values of SAPO are associated with less critical conditions, which would result in smaller economic benefits. Figure 6b shows the distribution of the elementary sections of 1 km according to the SAPO. According to the figure, 18 sites exhibit a positive SAPO value, meaning a potential economic benefit from intervention due to initial critical safety conditions.