Data Handling: Good Practices in the Context of Naturalistic Driving Studies

Christelle Al Haddad*, Md Rakibul Alam, Eleonora Papadimitriou, Tom Brijs, Constantinos Antoniou

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

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Abstract

Naturalistic driving studies (NDS) have recently gained attention as a way of instrumenting vehicles in an unobtrusive way and collecting driving data over long periods of time. Aiming at eventually modeling driving behavior, NDS are often a part of larger scale studies. These studies involve several stakeholders who are responsible for different components of the data collection and analysis, and thus are inevitably confronted with challenges in the data management pipeline. The aim of this paper is to develop standard protocols that could be used as guidelines for data handling in the context of NDS. In the development of these protocols, we first review data handling strategies used in previous studies, focusing on data collection, preparation, storage, as well as ethical and legal considerations. This review helps us draw lessons, based on which methods are developed to answer the gaps and challenges arising from handling NDS data. We then introduce a case study, the i–DREAMS project, to show the applicability of the data handling framework. Finally, we showcase standard protocols for data handling, that could serve as data handling guidelines for future studies.
Original languageEnglish
Pages (from-to)95-102
Number of pages8
JournalTransportation Research Procedia
Volume78
DOIs
Publication statusPublished - 2024
Event25th Euro Working Group on Transportation Meeting, EWGT 2023 - Santander, Spain
Duration: 6 Sept 20238 Sept 2023

Keywords

  • naturalistic driving studies
  • data handling
  • standard protocols
  • safer roads
  • efficient mobility
  • transportation technology

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