PSI - Issue 24

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

433

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

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Fig. 10. Impact configurations for case study 1-3, as a function of the intervention logic.

The outcomes in terms of IR for each case study are reported in Table 3, based on the logic selected for activation. Coherently with the above-expressed concepts, the adaptive logic implies a lower IR value in comparison to the other types of intervention logic. The maximum benefit deriving from the use of the criteria is evidenced in case study 1: IR deriving from the use of the adaptive logic is equal to 4% ( ∆ V = 16 km / h, near side impact), instead of 34% obtained by the full braking intervention ( ∆ V = 32 km / h, side impact).

Table 3. Outcomes in terms of IR associated with each case study, based on the ADAS logic for activation. Case study Intervention

IR

No intervention 100% braking

9%

1

34%

Adaptive intervention

4%

No intervention 100% braking

20% 41% 19%

2

Adaptive intervention

No intervention 100% braking

1%

3

16%

Adaptive intervention

1%

5. Conclusions

The present work analyses solutions, based on criteria for the minimization of injury risk (IR) and clearance be tween vehicles, for activation of advanced driver assistance systems (ADAS) to be embedded in an automated driving system (ADS). The features and tools required for the application of such criteria to adaptive logic are highlighted, which allows the ADAS to adapt to the scenario evolution. Three case studies are examined to demonstrate the criteria e ff ectiveness, comparing the solutions with current types of ADAS activation logic.