Cover Image

Assessing Driving Risk Through Unsupervised Detection of Anomalies in Telematics Time Series Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chan, Ian Weng, Badescu, Andrei L., Lin, X. Sheldon
Format:	Preprint
Published:	2024
Subjects:	Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data Mining of Telematics Data: Unveiling the Hidden Patterns in Driving Behaviour
by: Chan, Ian Weng, et al.
Published: (2023)

A Portfolio-Anchored Frequency-Severity Risk Index for Trip and Driver Assessment Using Telematics Signals
by: Lee, Jongtaek, et al.
Published: (2026)

Claim Reserving via Inverse Probability Weighting: A Micro-Level Chain-Ladder Method
by: Calcetero-Vanegas, Sebastian, et al.
Published: (2023)

Effective experience rating for large insurance portfolios via surrogate modeling
by: Calcetero-Vanegas, Sebastian, et al.
Published: (2022)

Marked Cox Models for IBNR Claims Count: Continuous and Discretized Approaches with Dirichlet-Driven Reporting Delays
by: Abdelrahman, Hassan, et al.
Published: (2024)

Integrating Spatial and Temporal Effects in Seat-Belt Compliance Assessment with Telematics Data
by: Dumka, Ashutosh, et al.
Published: (2025)

anomaly : Detection of Anomalous Structure in Time Series Data
by: Fisch, Alex, et al.
Published: (2020)

Static marginal expected shortfall: Systemic risk measurement under dependence uncertainty
by: Chen, Jinghui, et al.
Published: (2025)

Time-Dependent Pseudo $\boldsymbol{R^2}$ for Assessing Predictive Performance in Competing Risks Data
by: Zhuang, Zian, et al.
Published: (2025)

On Robust Inference in Time Series Regression
by: Baillie, Richard T., et al.
Published: (2022)

Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
by: Lau, Matthew, et al.
Published: (2025)

A Population Sampling Framework for Claim Reserving in General Insurance
by: Vanegas, Sebastian Calcetero, et al.
Published: (2025)

Time-Series Anomaly Classification for Launch Vehicle Propulsion Systems: Fast Statistical Detectors Enhancing LSTM Accuracy and Data Quality
by: Engelstad, Sean P., et al.
Published: (2026)

Tail Risk Analysis for Financial Time Series
by: Kiriliouk, Anna, et al.
Published: (2024)

Assessing the Operational Viability of Foundation Models for Time Series Forecasting
by: Soni, Kavin, et al.
Published: (2026)

Assessing the Shortfall Risk of GB Electricity Grid using Shifts in Winter Weather Conditions
by: Bhattacharya, Aninda, et al.
Published: (2026)

Spherically Embedded Time Series with Unknown Trend and Periodic Components
by: Xu, Jiazhen, et al.
Published: (2026)

Multiple Imputation of Hierarchical Nonlinear Time Series Data with an Application to School Enrollment Data
by: Liu, Daphne H., et al.
Published: (2024)

Using Time Series Measures to Explore Family Planning Survey Data and Model-based Estimates
by: Akinfenwa, Oluwayomi, et al.
Published: (2026)

Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes
by: Ghosh, Shuvrarghya, et al.
Published: (2025)

Assessing Time Series Correlation Significance: A Parametric Approach with Application to Physiological Signals
by: Medrano, Johan, et al.
Published: (2024)

A Beta-GAM Hidden Markov Model for Proportion Time Series
by: Nigri, Andrea, et al.
Published: (2026)

Age-Specific Logistic Regression with Complex Event Time Data
by: Haoxuan, et al.
Published: (2026)

Modeling Information Blackouts in Missing Not-At-Random Time Series Data
by: Sunesh, Aman, et al.
Published: (2026)

Privacy-Preserving Line Outage Detection in Distribution Grids: An Efficient Approach with Uncompromised Performance
by: Xiao, Chenhan, et al.
Published: (2023)

PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Section Data
by: Rauh, Adam, et al.
Published: (2025)

Composite Safety Potential Field for Highway Driving Risk Assessment
by: Zuo, Dachuan, et al.
Published: (2025)

Multivariate Time Series Data Imputation via Distributionally Robust Regularization
by: Liao, Che-Yi, et al.
Published: (2026)

Modelling Loss of Complexity in Intermittent Time Series and its Application
by: Li, Jie, et al.
Published: (2024)

Assessing Reporting Delays in ACLED Conflict Event Data
by: Razakason, Faniry A., et al.
Published: (2026)

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data
by: Hasan, Nazmul, et al.
Published: (2024)

Online Sequential Leveraging Sampling Method for Streaming Autoregressive Time Series with Application to Seismic Data
by: Xie, Rui, et al.
Published: (2025)

An Evaluation of Calibrated and Uncalibrated High-Resolution RGB Data in Time Series Analysis for Coal Spoil Characterisation: A Comparative Study
by: Thiruchittampalam, Sureka, et al.
Published: (2024)

Predicting Bad Goods Risk Scores with ARIMA Time Series: A Novel Risk Assessment Approach
by: Gond, Bishwajit Prasad
Published: (2025)

Changepoint Detection in Categorical Time Series with Application to Daily Total Cloud Cover in Canada
by: Li, Mo, et al.
Published: (2026)

COSMOS: A Data-Driven Probabilistic Time Series simulator for Chemical Plumes across Spatial Scales
by: Nag, Arunava, et al.
Published: (2025)

Bayesian Optimization of Sample Entropy Hyperparameters for Short Time Series
by: Blanks, Zachary, et al.
Published: (2024)

tsbootstrap: Enhancing Time Series Analysis with Advanced Bootstrapping Techniques
by: Gilda, Sankalp, et al.
Published: (2024)

Rethinking Nonstationarity in Time Series: A Deterministic Trend Perspective
by: Abdikhadir, Zhandos, et al.
Published: (2025)

How Much Is Too Much? Adaptive, Context-Aware Risk Detection in Naturalistic Driving
by: Kalantari, Amir Hossein, et al.
Published: (2025)