## 6 Human Perception of Severity and Objective Measures
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & **B** & **Std. Error** & \multicolumn{2}{c}{**Hypothesis Test**} & \multicolumn{2}{c}{**Elasticity (Individual**} \\ \cline{3-6}  & & **Wald Chi-Square** & **df** & **Sig.** & **Percentage Contribution)** \\ \hline Threshold & [Severity = 2.00] & \(-\)10.200 & 1.0010 & 103.833 & 1 & 0.000 & \\ \hline  & [Severity = 1.00] & \(-\)0.294 & 0.9813 & 0.090 & 1 & 0.764 & \\ \hline \(T_{2}\left(T_{2}^{min}\right)\) & \(-\)0.570 & 0.1037 & 30.256 & 1 & 0.000 & \(-\)0.205 \\ \hline \(D_{2}\left(D_{2}^{min}\right)\) & \(-\)0.473 & 0.1184 & 15.953 & 1 & 0.000 & \(-\)0.1822 \\ \hline \(D_{1}\left(D_{2}^{min}\right)\) & \(-\)2.888 & 0.4982 & 33.602 & 1 & 0.000 & \(-\)0.3514 \\ \hline \(D_{1}\left(T_{1}\right)\) & \(-\)0.408 & 0.0932 & 19.186 & 1 & 0.000 & \(-\)0.1982 \\ \hline V \(\left(T_{2}^{min}\right)\) & 0.334 & 0.0890 & 14.090 & 1 & 0.000 & 0.213 \\ \hline \(D_{R}\left(T_{2}^{min}\right)\) & \(-\)0.333 & 0.0946 & 12.391 & 1 & 0.000 & \(-\)0.111 \\ \hline PET (\(T_{2}\)) & \(-\)0.877 & 0.3843 & 5.212 & 1 & 0.002 & \(-\)0.197 \\ \hline EA & 1.143 & 0.2880 & 15.747 & 1 & 0.000 & 0.2429 \\ \hline  & & AIC = 624 & BIC = 792 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: MODEL A.  
variable. The aim was to determine if the presence of evasive actions held statistical significance in the model. The model can be represented as below:  
MODEL A: **Severity rating by human observers (Entire dataset = 1141)-**Indicators from moments: \((T_{2}^{min})\), \((D_{2}^{min})\), \((T_{1})\), \((T_{2})\), class variable (EA). The proxy indicator linked to evasive behavior, as demonstrated in Model A, was deemed significant and ranked second in significance, with the first being the distance. It appears that the pertinent information contained in the earliest conditions of a problem can be used to determine how serious it is. The dataset was then divided into two subgroups: the first subset is where evasive action was observed in one or both road users during an interaction, and the second subset is where no evasive action was observed by either of the road users. Using these subsets of data, two more models (models B and C) were then developed using the same set of explanatory variables. The aim was to examine whether the same \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & \multirow{2}{*}{**B**} & \multirow{2}{*}{**Std. Error**} & \multicolumn{2}{c}{**Hypothesis Test**} & \multicolumn{2}{c}{**Elasticity**} \\ \cline{5-8}  & & & **Wald Chi-Square** & **df** & **Sig.** & **(Individual Percentage Contribution)** \\ \hline Threshold & [Severity = 2.00] & \(-\)22.792 & 0.8587 & 704.498 & 1 & 0.000 & \\ \hline  & [Severity = 1.00] & \(-\)9.885 & 0.4568 & 468.193 & 1 & 0.000 & \\ \hline \(T_{2}\)\((T_{2}^{min})\) & \(-\)0.789 & 0.1154 & 46.717 & 1 & 0.000 & \(-\)0.169 \\ \hline \(D_{R}\)\((D_{2}^{min})\) & \(-\)0.263 & 0.0981 & 7.215 & 1 & 0.004 & \(-\)0.098 \\ \hline \(D_{1}\)\((T_{1})\) & \(-\)8.486 & 0.7121 & 141.991 & 1 & 0.000 & \(-\)0.328 \\ \hline PET \((T_{2})\) & \(-\)1.591 & 0.2867 & 30.785 & 1 & 0.000 & \(-\)0.182 \\ \hline \multicolumn{8}{c}{AIC = 396} & \multicolumn{2}{c}{BIC = 512} \\ \hline \hline \end{tabular}
\end{table} 
Table 6: MODEL B.