Managing Big Data for Addressing Research Questions in a Collaborative Project on Automated Driving Impact Assessment

Abstract

While extracting meaningful information from big data is getting relevance, literature lacks information on how to handle sensitive data by different project partners in order to collectively answer research questions (RQs), especially on impact assessment of new automated driving technologies. This paper presents the application of an established reference piloting methodology and the consequent development of a coherent, robust workflow. Key challenges include ensuring methodological soundness and data validity while protecting partners’ intellectual property. The authors draw on their experiences in a 34-partner project aimed at assessing the impact of advanced automated driving functions, across 10 European countries. In the first step of the workflow, we captured the quantitative requirements of each RQ in terms of the relevant data needed from the tests. Most of the data come from vehicular sensors, but subjective data from questionnaires are processed as well. Next, we set up a data management process involving several partners (vehicle manufacturers, research institutions, suppliers and developers), with different perspectives and requirements. Finally, we deployed the system so that it is fully integrated within the project big data toolchain and usable by all the partners. Based on our experience, we highlight the importance of the reference methodology to theoretically inform and coherently manage all the steps of the project and the need for effective and efficient tools, in order to support the everyday work of all the involved research teams, from vehicle manufacturers to data analysts.

Exploiting Big Data for Experiment Reporting: The Hi-Drive Collaborative Research Project Case

“…The context and motivation of this research come from the automated driving (AD) industrial sector, which represents a highly significant investigation domain given the huge amount of research that is being carried out in the field (e.g., [ 4 , 5 , 6 , 7 ]). In the L3Pilot project [ 8 ], dedicated to piloting SAE level 3 automated driving functions (ADFs), we studied how to organize a robust workflow for quantitatively addressing research questions (RQs) in a collaborative project sharing sensitive data among various partners, while ensuring methodological soundness and data validity, and protecting partners’ intellectual property (IP) [ 9 , 10 ]. This process was driven by a well-established reference methodology for large scale pilots and field operational automotive tests, namely Field opErational teSt supporT Action (FESTA) [ 11 ].…”

“…Given the strong similarities of the experimental processes, the Hi-Drive reference architecture builds on the L3Pilot data architecture [ 9 , 10 ]. However, a critical assessment of the L3Pilot experience stressed the need for improving the periodical reporting on the state of the project in the different pilot sites, which suffered difficulties in extracting and managing KPIs (e.g., how many kilometers were travelled in the period, in what road type; how many persons took part in the tests, with what roles, etc.).…”

Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line’s Digital Twin by Using Color Sensor

“…The idea of an intelligent factory can be defined in terms of Industry 4.0 concepts by applying the above areas. Theoretically, it is based on nine technological pillars: the industrial Internet of Things (IoT) in the form of CPS, big data and analytics, product lifecycle management (PLM) systems, digital manufacturing, cloud computing, augmented reality, autonomous or collaborative robots, additive manufacturing and cybersecurity [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ].…”

Recent Trends on Applications of Electronics Pervading the Industry, Environment and Society

“…The Special Issue is characterized by 13 original research papers [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ] that we briefly introduce in the following.…”

“…Finally, paper thirteen [ 13 ], “Managing Big Data for Addressing Research Questions in a Collaborative Project on Automated Driving Impact Assessment”, is authored by Bellotti et al, an international group of researchers collaborating in the L3Pilot project, which is the piloting of Society of Automotive Engineers (SAE) level 3 automated vehicle functions.…”