Characterization of Stable-Health Older Drivers Using Low-Speed Driving Maneuvers From In-Vehicle Sensor Data
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The Candrive study aims to improve the current practices of screening elderly drivers in Canada by identifying predictors of motor vehicle collisions from monitoring their daily driving behaviours using in-vehicle sensors. The thesis objective was to characterize the baseline behaviour of stable-health older drivers by proposing parameters of interest for detecting changes in behaviour and methods to differentiate drivers using their maneuvers. The in-vehicle sensor data from 12 stable-health drivers were processed, and a turn-identification algorithm with 97.7% accuracy was created for extracting four maneuvers: accelerating from stop, decelerating to stop, right turns, and left turns on 40 to 60 km/h roadways. Most of the drivers exhibited relatively steady month-to-month acceleration behaviours and lower accelerations in adverse driving conditions, which represented their typical driving behaviours. Drivers can be differentiated by the driving patterns from their maneuvers using a multi-expert classifier, which may be applicable for detecting changes in driving behaviour.
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Copyright © 2018 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2018
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fung-characterizationofstablehealtholderdrivers.pdf | 2023-05-05 | Public | Download |