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Volume: 32 | Article ID: art00018
Metrology Impact of Advanced Driver Assistance Systems
  DOI :  10.2352/ISSN.2470-1173.2020.16.AVM-202  Published OnlineJanuary 2020

Metrological applications to road environment are usually focused on the characterization of the road, considering as measurands several characteristics related to the road as a whole or the performances of single components, like the road surface, lighting systems, active and/or passive signaling and obviously vehicles equipment. In current standards approach, driving on the road means to navigate ”visually” (for a human being driver), the characterizations are mostly photometric performances oriented for given reference conditions and reference observer (photometric observer observing the road from assigned points of view, with given spectral sensitivity). But considering the present and future technological trends and knowledge on visual performances, characterizations based on only photometric quantities in reference conditions as described in the current standards would be not fully suitable, even for human driver visual needs. Nowadays research on components and systems for advanced driver assistance are evolving, following different paths toward different solutions: it is not possible, nor useful to define strict constraints as it has been done previously for road applications measurements. The paper presents the current situation of metrological characterization of road environment and components, on laboratory and on site using mobile high efficiency laboratories, and suggests to use ADAS (Advanced Driver Assistance System) for diffuse mapping of road characteristics for a better understanding of the road environment and maintenance. The suggestion has the additional advantage of minimizing measurement costs, but for its full applicability, the reliability and metrological performances of installed devices and of the measurements performed by ADAS are a priority.

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Paola Iacomussi, "Metrology Impact of Advanced Driver Assistance Systemsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines,  2020,  pp 202-1 - 202-6,

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