Abstract
The data presented in this article are related to the research manuscript “Predictors of older drivers’ involvement in rapid deceleration events”, which investigates potential predictors of older drivers’ involvement in rapid deceleration events including measures of vision, cognitive function and driving confidence (A. Chevalier et al., 2016) [1]. In naturalistic driving studies such as this, when sample size is not large enough to allow crashes to be used to investigate driver safety, rapid deceleration events may be used as a surrogate safety measure. Naturalistic driving data were collected for up to 52 weeks from 182 volunteer drivers aged 75–94 years (median 80 years, 52% male) living in the suburban outskirts of Sydney. Driving data were collected using an in-vehicle monitoring device. Accelerometer data were recorded 32 times per second and Global Positioning System (GPS) data each second. To measure rapid deceleration behavior, rapid deceleration events (RDEs) were defined as having at least one data point at or above the deceleration threshold of 750milli-g (7.35m/s2). All events were constrained to a maximum 5s duration. The dataset provided with this article contains 473 events, with a row per RDE. This article also contains information about data processing, treatment and quality control. The methods and data presented here may assist with planning and analysis of future studies into rapid deceleration behaviour using in-vehicle monitoring.
Highlights
The data presented in this article are related to the research manuscript “Predictors of older drivers’ involvement in rapid deceleration events”, which investigates potential predictors of older drivers’ involvement in rapid deceleration events including measures of vision, cognitive function and driving confidence
In naturalistic driving studies such as this, when sample size is not large enough to allow crashes to be used to investigate driver safety, rapid deceleration events may be used as a surrogate safety measure
Table describing variables, two figures The in-vehicle monitoring device consisted of a C4D Data Recorder with an external Global Positioning System (GPS) receiver
Summary
Table describing variables, two figures The in-vehicle monitoring device consisted of a C4D Data Recorder with an external GPS receiver. Accelerometer data were recorded at 32 Hz (32 times per second). Processed, assessed for quality control Accelerometer data were treated to address calibration and wandering baseline. The data provided in this manuscript may be used to calculate sample sizes for other studies investigating rapid deceleration behavior. Methodological considerations are reported including treating accelerometer data to address calibration and wandering baseline issues, monitoring inactivity, and quality control. This data could be considering in future meta-analysis combining this data about older drivers’. The dataset contains one row per rapid deceleration event (Supplementary Table 1). Of one participant's driving, and Fig. 2 depicts accelerometer recordings during a RDE before and after a re-calibration adjustment was applied
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