Guidelines for data quality assurance

The UDRIVE project aims to colle ct on the region of 100,000 hours of naturalistic driving data in order to support the analysis related to o Crash causation, crash risk and normal driving o Distraction and inattention o Vulnerable road users o Driving styles related to eco-driving This document contains information relevant to data quality assurance for the UDRIVE project. Good quality data is a fundamental requirement for good quality analysis and data quality should be considered at all stages of the data processing chain: o Data Acquisition System Installation o During data collection o Database management • Data preprocessing • Data post-processing In order to deliver high quality data as an outcome from the UDRIVE project actions have been undertaken at each stage of the chain, following generic guidelines for data quality