Space Occupancy Index (SOI)

Description

The SOI defines a personal space for each actor and counts violations by other participants while setting them in relation to the analyzed period of time [Tsukaguchi1987] [Ogawa2007] [Johnsson2018]. For each actor \(A_i\) at time \(t\), a personal space \(\mathit{Sp}(A_i, t)\) is defined. At time \(t\), if there exists some \(A_j \neq A_i\) s.t. \(\mathit{Sp}(A_i, t) \cap \mathit{Sp}(A_j, t) \neq \emptyset\), a violation of the personal space of \(A_i\) is given. The number of conflicts is then given as \(C(A_1, \mathcal{A}, t) = \sum_{A_j \in \mathcal{A}\setminus\{A_1\}} [\mathit{Sp}(A_1) \cap \mathit{Sp}(A_j) \neq \emptyset]\), where \([\cdot]\) denotes the Iverson bracket. Thus, for a given scenario in the time interval \([t_0, t_e]\), the conflict index is defined as

\[\mathit{SOI}(A_1,\mathcal{A}) = \sum_{t=t_0}^{t_e} C(A_1, \mathcal{A}, t).\]

SOI was introduced for bicycles and pedestrians, however, it is possible to formulate a similar concept for road vehicles.

Properties

Run-time capability

Yes, but only retrospectively

Target values

No

Subject type

Originally defined for VRUs, could be extended to road vehicles

Scenario type

Any scenario

Inputs

Actor type, size of safe space depending on type

Output scale

\([0,\infty)\), hertz (1/s), ratio scale

Reliability

Medium, due to the nominal nature of the conflict definition, which leads to fluctuations if vehicles exist close the boundaries of personal space

Validity

Medium, since temporal and dynamical aspects are ignored due to binary evaluation; no empirical analysis available

Sensitivity

Medium, as already a single safe space violation can lead to an accident

Specificity

Medium, as multiple safe space violations are associated but with but not necessarily causative for accidents

Prediction model

None, since a-posteriori