Smartphones vs. in-vehicle data acquisition systems as tools for naturalistic driving studies: A comparative review. (November 2020)

• Record Type: Journal Article
• Authors: Grimberg, Einat; Botzer, Assaf; Musicant, Oren
• Is Part Of: Safety science. Volume 131(2020)
• Publication Date: 2020-11
• Subjects: Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2020.104917
• Languages: English
• ISSNs: 0925-7535

Abstract

Highlights: Naturalistic driving studies (NDS) employ data acquisition systems (DAS). Smartphones are gaining interest as DAS for NDS. We compare smartphones and in-vehicle DAS across eleven key attributes. We discuss the implications for using smartphone DAS for NDS. Abstract: Naturalistic driving studies (NDS) are increasingly being used to investigate driver on-road behavior. In parallel, smartphones are gaining interest as data acquisition systems (DAS) in NDS instead of costly in-vehicle DAS. However, smartphone and in-vehicle DAS differ across several attributes and no current document outlines the implications of using smartphones as DAS in NDS. In this document, we present a comparative review of the advantages and disadvantages of using smartphone and in-vehicle DAS in NDS and discuss their implications. In addition, we present a brief account on prospective technological developments that might have further implications for using smartphones for studying and advancing road safety. Researchers and practitioners can use this review as a general guide to decide which DAS (smartphone or in-vehicle) to use in their NDS. For example, smartphones would be a cost-effective alternative for studying driving style (e.g., braking and speeding), but an inferior alternative to in-vehicle DAS for reconstructing crashes or near crashes and for studying short-term relationships between events (e.g., smartphone usage and hard braking). Researchers and practitioners can also use this review as an aid for the design of NDS with smartphones. For example, we show that it would be advisable to use beacons to know if participants were driving their vehicle or riding the bus, and that data completeness and accuracy would depend on battery charge and using a cradle. Prospective technologies might mitigate the shortcomings that we have outlined and might even dim the distinction between the different types of DAS.