Remote Driver Identification Using Minimal Sensory Data

• Published in: IEEE communications letters Vol. 19; no. 10; pp. 1706 - 1709
• Main Authors: Saiprasert, Chalermpol, Thajchayapong, Suttipong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometers; Accuracy; Algorithms; Driver Identification; Driving Behaviour Signals; Global Positioning System; Performance evaluation; Real-time systems; Sampling; Sensors; Vehicles; Driver identification; driving behavior signals
• ISSN: 1089-7798; 1558-2558
• DOI: 10.1109/LCOMM.2015.2459701

This letter proposes a driver identification algorithm developed for using minimal information transmitted in vehicle-to-vehicle (V2V) environment based on the assumption that each driver has his/her own unique driving behavior characteristics hidden in conventional driving behaviour signals. Performance evaluation using real-world data shows that the proposed algorithm accurately identifies three drivers in 15 trips using only two acceleration signals at a sampling rate much lower than the one used in previous study. Furthermore, it is shown that the proposed algorithm is able to perform driver identification within a small connectivity time in a scenario where driving behavior signals of are transmitted via a V2V communication environment in a streaming manner.