On data security and analysis platforms for analysis of naturalistic driving data
Paper i proceeding, 2011

Studies involving naturalistic driving data, of which Naturalistic Field Operational Tests (N-FOTs) are a subset, are becoming increasingly important for understanding the factors influencing accident causation as well as for the development and evaluation of active safety systems. The methodology project FESTA developed a handbook on how to plan and implement FOTs. This handbook has been extensively used as a guideline in the euroFOT project. However, “the devil is in the details” when implementing e.g. the platforms for data security and analysis in projects which deal with analysis of large amounts of sensitive naturalistic driving data, such as euroFOT. That is, although a guideline such as FESTA is used, how the details are implemented is what makes the implementation a success or not. This paper is a case description of the implementation of the data security and analysis platform used for euroFOT (and other naturalistic data projects) at the SAFER Vehicle and Traffic Safety Centre. The paper covers aspects ranging from physical access to analysis rooms and corresponding digital access, via the platforms for pre-processing of data, to the platforms for information extraction for hypothesis analysis and statistics. The considerations in the design and choice of these platforms include subjects (drivers) privacy concerns, industry commercial concerns, as well as the needs and requirements from the analysis.

Författare

Jonas Bärgman

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Helena Gellerman

Jordanka Kovaceva

Rasmus Nisslert

Selpi Selpi

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Erik M Steinmetz

Marco Dozza

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Proceedings of the 8th European Congress and Exhibition on Intelligent Transport Systems and Services, June 2011, Lyon

Drivkrafter

Hållbar utveckling

Innovation och entreprenörskap

Styrkeområden

Transport

Ämneskategorier

Data- och informationsvetenskap

Datavetenskap (datalogi)

Fundament

Grundläggande vetenskaper