D3.5 Standard protocol for handling big data Safe tolerance zone calculation and interventions for driver-vehicle-environment interactions under challenging conditions

Abstract

The i-DREAMS project intends to develop a framework for the definition, development, testing and validation of a context-aware safety envelope for driving called the ‘Safety Tolerance Zone’. Taking into account driver background factors and real-time risk indicators associated with the driving performance as well as the driver state and driving task complexity indicators, a continuous real-time assessment will be made to monitor and determine if a driver is within acceptable boundaries of safe operation. Moreover, safety-oriented interventions will be developed to inform or warn the driver in real-time as well as on an aggregated level after driving, through an app-and web-based gamified coaching platform (post-trip intervention). Furthermore, a user-license Human Factors database with anonymised data from the simulator and field experiments will be developed. The conceptual framework of the i-DREAMS platform integrates aspects of monitoring (such as context, operator, vehicle, task complexity and coping capacity), to develop a Safety Tolerance Zone for driving. In-vehicle interventions and post-trip interventions will help to maintain the safety tolerance zone as well as provide feedback to the driver. This conceptual framework will be tested in simulator studies and three stages of on-road trials in Belgium, Germany, Greece, Portugal, and the United Kingdom (UK) with a total of 600 participants representing car, bus, truck, rail drivers. During the experiments, large amounts of data will be generated, from the different data collection tools, originating from different modes and countries. This “Big Data“ will inevitably need to follow guidelines that would specify how they could be best handled, and how they would pass from one entity to another while complying with legal and ethical regulations set out at a national, and EU level; these would be compliant with the GDPR regulations (2016/679), aiming to protect personal data, and ensuring that the proper framework is set out in case of agreement infringement. The aim of this deliverable is to therefore provide the necessary protocols for handling the generated big data, passing through the different steps from data collection, to data storage. Looking at the different collection phases, a specific indication would be given on special considerations that would be needed for other modes, where available. The specific objectives of this deliverable are therefore:  Provide a methodology for the handling of big data, based on learnings from previous studies/projects; particularly naturalistic driving studies (NDS) studies in Europe  Provide standard protocols for the handling of big data, informing i-DREAMS experiments on the procedures to be followed to best handle collected data, while complying with the necessary regulations and ethical considerations The standard protocols are to be continuously controlled throughout the i-DREAMS project, and would be in accordance to the data management plan (DMP), and the data and knowledge management committee; partners at different countries would be responsible for their own data collection, and obliged to follow the proper standards, while consulting with their national and local authorities. The protocols will checked for feasibility and maintainability and at the end of the project, a report will be drawn to identify issues that have or could have been improved, to serve as guidelines for future projects/research involving similar data collection.