Big Data Analysis of Canadian Drivers Using OBDII Sensor Data: The Impact of the Pandemic

Techniques to quantify driving skills and driving habits (e.g. duration and frequency of driving) are critical to the analysis of driving safety. Metrics related to driving are key to the analyses of safety topics such as differences in driving throughout the lifespan. An extensive literature examines such factors as novice/expert differences or the declines in driving ability that may occur with cognitive aging. Big Data analysis techniques can now be applied to the datasets being captured by automakers and insurance companies through in-car recording sensors to better understand changes in driving activity and patterns. These datasets include very large samples of drivers of all ages enabling the comparative study of all drivers including comparison of novice, and older driver groups. This paper leverages one such dataset to examine the driving patterns of Canadian drivers over one year while COVID 19 pandemic precautions were in effect. Specifically, one year of data for 7677 vehicles in Canada that have a single insured driver is examined. The dataset was captured during the pandemic and a general reduction in driving associated with pandemic precautions was observed. The report suggests that for several age groups, reductions in driving were larger for males than females.