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
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