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

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, the authors 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. The authors then introduce a case study, the i–DREAMS project, to show the applicability of the data handling framework. Finally, the authors showcase standard protocols for data handling, that could serve as data handling guidelines for future studies.

• Record URL:
  • https://doi.org/10.1016/j.trpro.2024.02.013
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2352146524000668
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2024 The Author(s). Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Al Haddad, Christelle
  • Alam, Md Rakibul
  • Papadimitriou, Eleonora
  • Brijs, Tom
  • Antoniou, Constantinos
• Conference:
  • 25th Euro Working Group on Transportation Meeting (EWGT 2023)
  • Location: Santander , Spain
  • Date: 2023-9-6 to 2023-9-8
• Publication Date: 2024

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 95-102
• Serial:
  • Transportation Research Procedia
  • Volume: 78
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Case studies; Data management; Guidelines; Standards
• Subject Areas: Data and Information Technology; Highways;

Filing Info

• Accession Number: 01918345
• Record Type: Publication
• Files: TRIS
• Created Date: May 14 2024 11:44AM