Assessment of the Skills of Car Drivers Based on the Processing of Telematics Monitoring Data

• Published in: Systems of Signals Generating and Processing in the Field of on Board Communications (Online) pp. 1 - 5
• Main Authors: Pletnev, M. G., Smirnov, P. I., Karelina, E. A., Subbotin, B. S., Silakov, A. V.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 12.03.2024
• Subjects: assessment of drivers' skills; Automobiles; Connected vehicles; Costs; Prediction algorithms; road safety; Software; Software reliability; telematic data; Telematics; transport mobility; urban transport
• ISSN: 2768-0118
• DOI: 10.1109/IEEECONF60226.2024.10496799

Based on statistical data on the driving characteristics of vehicles obtained as a result of long-term observation of 19 trucks and cars, the article analyzes assessment methods built into telematics software. It is shown that standard methods for assigning driver ratings are not indicative, as they give contradictory results when compared. Based on well-known approaches, a method for assessing the actions of drivers is proposed based on a comprehensive automated assessment of actions and driving characteristics, which gives more reliable results. From the point of view of predictive determination of states and behavior patterns of vehicle drivers, it is proposed to use the MSET algorithm, and boundary data on the criteria for assessing individual behavior patterns is also provided. The proposed method can be proposed to implement an automated system for assessing driver behavior patterns at minimal cost based on standard telematics information received from connected vehicles.