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Optimising driver profiling through behaviour modelling of in-car sensor and global positioning system data
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Ahmadi-Assalemi, Gabriela, al-Khateeb, Haider M., Maple, Carsten, Epiphaniou, Gregory, Hammoudeh, Mohammad, Jahankhani, Hamid and Pillai, Prashant (2021) Optimising driver profiling through behaviour modelling of in-car sensor and global positioning system data. Computers and Electrical Engineering, 91 . 107047. doi:10.1016/j.compeleceng.2021.107047 ISSN 0045-7906.
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WRAP-optimising-driver-profiling-through-behaviour-modelling-in-car-sensor-global-positioning-system-data-Epiphaniou-2020.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1697Kb) | Preview |
Official URL: https://doi.org/10.1016/j.compeleceng.2021.107047
Abstract
Connected cars have a massive impact on the automotive sector, and whilst this catalyst and disruptor technology introduce threats, it brings opportunities to address existing vehicle-related crimes such as carjacking. Connected cars are fitted with sensors, and capable of sophisticated computational processing which can be used to model and differentiate drivers as means of layered security. We generate a dataset collecting 14 hours of driving in the city of London. The route was 8.1 miles long and included various road conditions such as roundabouts, traffic lights, and several speed zones. We identify and rank the features from the driving segments, classify our sample using Random Forest, and optimise the learning-based model with 98.84% accuracy (95% confidence) given a small 10 seconds driving window size. Differences in driving patterns were uncovered to distinguish between female and male drivers especially through variations in longitudinal acceleration, driving speed, torque and revolutions per minute.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA75 (Please use QA76 Electronic Computers. Computer Science) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Library of Congress Subject Headings (LCSH): | Automated vehicles, Internet of things, Mobile communication systems, Motor vehicles -- Automatic control, Vehicular ad hoc networks (Computer networks), Global Positioning System | ||||||||
| Journal or Publication Title: | Computers and Electrical Engineering | ||||||||
| Publisher: | Elsevier | ||||||||
| ISSN: | 0045-7906 | ||||||||
| Official Date: | May 2021 | ||||||||
| Dates: |
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| Volume: | 91 | ||||||||
| Article Number: | 107047 | ||||||||
| DOI: | 10.1016/j.compeleceng.2021.107047 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 18 June 2020 | ||||||||
| Date of first compliant Open Access: | 3 March 2022 | ||||||||
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