Conflict Index (CI)¶
Description¶
The conflict index enhances the acs{PET} metric with a collision probability estimation as well as a severity factor [Alhajyaseen2015]. For this, the estimated kinetic energy that would have been released assuming a hypothetical collision between \(A_1\) and \(A_2\) at their states when entering (\(A_2\)) resp. exiting (\(A_1\)) the conflict area is estimated:
where the denominator is a collision probability estimation.
Therefore, it is proposed that the actual collision probability is proportional to \(e^{- \beta \mathit{PET}(A_1, A_2, \mathit{CA})}\) with \(\beta\) being a calibration factor dependent on the scenario factors, e.g. country, road geometry, or visibility and \([\beta] = \text{s}^{-1}\). The nominator represents a collision severity measure, where \(\alpha \in [0,1]\) is again a calibration factor for the proportion of energy that is transferred from the vehicle’s body to its passengers and \(\Delta K_e\) is the predicted absolute change in kinetic energy before and after the predicted collision.
\(\Delta K_e\) is estimated based on the masses as well as velocities and angles at time of entering (\(A_2\)) resp. exiting (\(A_1\)) the conflict area.
Properties¶
Run-time capability¶
None, since PET can only be determined a-posteriori
Target values¶
None given
Subject type¶
Any two actors, but most suitable for road vehicles (automated and humans)
Scenario type¶
Any scenario with a conflict area (containing a potential intersection point)
Inputs¶
CA, \(\theta_1(t_{\mathit{exit}}(A_1,\mathit{CA}))\), \(\theta_2(t_{\mathit{entry}}(A_2,\mathit{CA}))\), \(v_1(t_{\mathit{exit}}(A_1,\mathit{CA}))\), \(v_2(t_{\mathit{entry}}(A_2,\mathit{CA}))\), \(m_1, m_2\), \(\mathit{PET}(A_1, A_2, \mathit{CA})\), calibration factors \(\alpha, \beta\)
Output scale¶
\((-\infty, \infty)\), joule (\(\text{kg}\cdot \text{m}^2 \cdot \text{s}^{-2}\)), ratio scale
Reliability¶
Comparable to PET
Validity¶
Initial validation was performed, exponential relationship to number of collisions over varying intersections was shown with a reasonably high coefficient of determination [Alhajyaseen2015]
Sensitivity¶
Depends on the sensitivity of PET, but potentially increased due to consideration of severity
Specificity¶
Depends on the specificity of PET, but potentially increased due to consideration of severity
Prediction model¶
None, since a-posteriori