Proportion of Stopping Distance (PSD)#

Description#

The PSD metric, proposed by Allen et al., is defined as the distance to a conflict area CA divided by the MSD [Allen1978] [Mahmud2017] [Guido2011] [Astarita2012]. Therefore,

\[\mathit{PSD}(A_1,\mathit{CA},t) = \frac{d(p_1(t),p_\mathit{CA}(t))}{\text{MSD}(A_1,t)} \text{, } \text{MSD}(A_1,t) = \frac{\|v_1(t)\|_2^2}{2|a_{1,\mathit{long,min}}(t)|}\,.\]

Properties#

Run-time capability#

Yes

Target values#

< 1 (point of no return), 1.5 (scenario classification) [Huber2020]

Subject type#

Road vehicles (automated and human)

Scenario type#

Any scenario with a conflict area (containing a potential intersection point)

Inputs#

CA, position \(p_1\), velocity \(v_1\), maximal deceleration of ego \(a_{1,\mathit{long,min}}\)

Output scale#

\([0, \infty)\), number, ratio scale

Reliability#

Can be reduced if actor tries to bypass conflict area in order to avoid collision, reliability higher than ET [Allen1978]

Validity#

Low, depending on validity of the conflict area; found to have lowest relation to collision history for an unprotected left turn scenario with a static CA [Allen1978]

Sensitivity#

High, assuming that the conflict area is defined as a dynamically changing predicted point of collision [Guido2011], reduced otherwise

Specificity#

Low, if criticality is measured completely independent of other actors in the scenario, also low if defined relative to a predicted collision point [Guido2011]

Prediction model#

Time window#

Unbound, but usefulness depends on DMM

Time mode#

Linear time