Back to Search Start Over

Road Rage and Aggressive Driving Behaviour Detection in Usage-Based Insurance Using Machine Learning

Authors :
Subramanian Arumugam
R. Bhargavi
Source :
International Journal of Software Innovation. 11:1-29
Publication Year :
2023
Publisher :
IGI Global, 2023.

Abstract

Driving behaviour is a critical issue in modern transportation systems due to the increasing concerns about the safety of drivers, passengers, and road users. Machine learning models are capable of learning driving patterns from sensor data and recognizing individuals by their driving behaviours. This paper presents a novel framework for aggressive driving detection and driver classification based on driving events identified from GPS data collected with smartphones and heart rate of the driver captured with a wearable device. The proposed system for road rage and aggressive driving detection (RAD) is realized with an integral framework with components for data acquisition, event detection, driver classification, and model interpretability. The system is implemented by generating a prediction model by training machine learning classifiers with a dataset collected in a cohort to classify drivers into good, unhealthy, road rage, and always bad. The proposed system is to improve road safety and to customize insurance premiums in the best interest of policy holders and insurance companies.

Details

ISSN :
21667179 and 21667160
Volume :
11
Database :
OpenAIRE
Journal :
International Journal of Software Innovation
Accession number :
edsair.doi...........1ea65d138bea1e45422a685f06dec0d2
Full Text :
https://doi.org/10.4018/ijsi.319314