Citation

Gulino MS, Fiorentino A, Vangi D. Eur. Transp. Res. Rev. 2022; 14(1): e3.

Copyright

(Copyright © 2022, European Conference of Transport Research Institutes, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1186/s12544-022-00527-4

PMID

unavailable

Abstract

Prospective and retrospective performance assessment of Advanced Driver Assistance Systems (ADASs) is fundamental to pilot future enhancements for active safety devices. In critical road scenarios between two vehicles where ADAS activation enables collision mitigation only, currently available assessment methodologies rely on the reconstruction of the impact phase consequent to the specific intervention on braking and steering: the velocity change sustained by the vehicle in the collision ($$\Delta V$$) is retrieved, so that IR decrease for the vehicle occupants can be obtained by appropriate Injury Risk (IR) models. However, information regarding the ADAS performance is available only after the impact phase reconstruction and not just as when the criticality occurs in the pre-impact phase: the best braking and steering alternative cannot be immediately envisaged, since a direct correlation lacks between the braking/steering intervention and IR.

Method
This work highlights an ADAS performance assessment method based on the disaggregation of Δ

Keywords

Adaptive logic; Closing velocity; Consumer program; Impact eccentricity; Injury risk; Velocity change (
Δ