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