PSI - Issue 24

Dario Vangi et al. / Procedia Structural Integrity 24 (2019) 423–436

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D. Vangi et al. / Structural Integrity Procedia 00 (2019) 000–000

Fig. 4. IR curves as a function of ∆ V , impact area and position of the occupant (modified from Jurewicz et al. (2016)).

Fig. 5. Map of outcomes for a generic critical scenario, which summarizes the values of IR associated with each braking and steering intervention by an adaptive ADAS.

clearance is defined by negative values of IR, the problem of finding the best intervention simplifies to the identification of minimum IR. Graphically, if green colored areas are present in the map (impact evitability), the system will activate preferring dark green areas (high clearance); in case only red colored areas are present (ICS), the system will intervene selecting light red areas (low IR).

2.3. Hardware-in-the-loop proposals

SiL functions can be converted in two di ff erent forms of hardware-in-the-loop (HiL), as a function of the final use: a tool to evaluate di ff erent types of ADAS logic (e.g., AEB, AES or their combination) or an actual ADAS to be implemented onboard the vehicle. In the first case, in which the objective is to compare the performances of di ff erent ADAS functions by simulation, calculation time is of low relevance; contrarily, in the second case, the adaptive ADAS must determine the outcomes associated with all possible interventions in a time which is compatible with the scanning time of the scenario. This requirement cannot currently be satisfied even employing a special purpose RODM: the