Methodology for ADAS Validation: Potential Contribution of Other Scientific Fields Which Have Already Answered the Same Questions

  • G. YahiaouiEmail author
  • P. Da Silva Dias
Conference paper
Part of the Lecture Notes in Mobility book series (LNMOB)


Since the 80s, the building of learn and test data bases for learning-based systems (i.e. neural networks) had to cope with problems of picking representative examples and measuring the generalization/the score of the system. And of course, real open world applications cannot be fully tested. It seems that artificial vision-based ADAS now discover the same question, and then, may use the same solutions, involving the same methodology (A.G.E.N.D.A.), using design of experiments and data analysis tools.


Factors of variability Testing Open world systems Methodology AGENDA Design of experiments Data analysis Efficiency Testing Validation 



Advanced Driver Assistance Systems

s/n ratio

signal/noise ratio


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.NEXYADSaint Germain en LayeFrance

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