Driver Identification Through Formal Methods
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3055347
Abstract: Recently, several research efforts have been focused on automotive safety, due to the increasing technology embedded in our vehicles. Research community have produced different methods aimed, for instance, to profile driver behaviour, starting from a… read more here.
Keywords: identification formal; formal methods; identification; driver identification ... See more keywords
Siamese Temporal Convolutional Networks for Driver Identification Using Driver Steering Behavior Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3151264
Abstract: Driver identification has shown sustainable development in recent years in a wide variety of applications including but not limited to security, personalization, fleet management, insurance telematics, or ride-hailing. However, the current progress suffers from several… read more here.
Keywords: steering behavior; identification; driver identification; behavior analysis ... See more keywords
Driver Identification Using Deep Generative Model With Limited Data
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2023.3240185
Abstract: The scarcity of driving data constrains the accuracy of deep learning (DL)-based driver identification methods in practical application scenarios. To address this issue, this study proposes a novel unsupervised deep generative model called the convolution… read more here.
Keywords: generative model; identification; driver identification; deep generative ... See more keywords
Combining Unsupervised Anomaly Detection and Neural Networks for Driver Identification
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DOI: 10.1155/2017/6057830
Abstract: This paper proposes an algorithm for real-time driver identification using the combination of unsupervised anomaly detection and neural networks. The proposed algorithm uses nonphysiological signals as input, namely, driving behavior signals from inertial sensors (e.g.,… read more here.
Keywords: anomaly detection; proposed algorithm; driver identification; neural networks ... See more keywords
Public Transport Driver Identification System Using Histogram of Acceleration Data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Advanced Transportation"
DOI: 10.1155/2019/6372597
Abstract: This paper introduces a driver identification system architecture for public transport which utilizes only acceleration sensor data. The system architecture consists of three main modules which are the data collection, data preprocessing, and driver identification… read more here.
Keywords: identification; identification system; driver identification; acceleration ... See more keywords