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The identification of characteristic individual driving behaviours is an emerging challenge that occurs within longitudinal studies of drivers to distinguish different drivers of a shared vehicle. It also has application in the insurance industry where insurance risk and associated owner premium depends on the diversity or lack thereof of drivers for a vehicle such as a vehicle driven/never driven...
The Candrive/Ozcandrive project is a long term study that is now entering its sixth year focused on improving the safety of older drivers. The study includes 256 older drivers in the Ottawa area and is an example of a longitudinal study that generates big data sensor information recorded from the participant vehicles. This paper uses the Can drive data and proposes solutions that would enable differential...
The accelerometer has become one of the most popular sensors in recent years due to its low cost and the widespread availability of smart phones that now contain three axis accelerometers. This paper proposes an adaptive drift calibration technique for accelerometer signals, correcting higher sampling rate accelerometers using lower sampling rate velocity and position measurements. Specifically, this...
This paper demonstrates the validity of vehicle acceleration/deceleration signals derived from 1Hz sampled GPS position and OBDII velocity sensors through comparison to 40Hz sampled accelerometer measurements. Measurement of driver acceleration and deceleration is important because it is a key measure of driving habits. Ideally, these measurements should not require the cost and complexity of installing...
This paper presents the analysis of all driving by a single (female) older diver over a one year period from the Candrive project. Data analytics techniques have been applied to this unique big data set that includes 1 Hz sampled Global Positioning System (GPS) and Geographic Information System (GIS) data and includes the analysis of 1562 trips covering 13,425 km. The driver is known to have stable...
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