EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset

• URL: http://arxiv.org/abs/2603.25955v1
• Date: Thu, 26 Mar 2026 22:47:45 GMT
• Title: EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset
• Abstract summary: EngineAD is a novel dataset comprising high-resolution sensor telemetry collected from a fleet of 25 commercial vehicles over a six-month period.<n>We preprocess the data into $300$-timestep segments of $8$ principal components and establish an initial benchmark using nine diverse one-class anomaly detection models.<n>Our experiments reveal significant performance variability across the vehicle fleet, underscoring the challenge of cross-vehicle generalization.
• Score: 7.231276782144985
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The progress of Anomaly Detection (AD) in safety-critical domains, such as transportation, is severely constrained by the lack of large-scale, real-world benchmarks. To address this, we introduce EngineAD, a novel, multivariate dataset comprising high-resolution sensor telemetry collected from a fleet of 25 commercial vehicles over a six-month period. Unlike synthetic datasets, EngineAD features authentic operational data labeled with expert annotations, distinguishing normal states from subtle indicators of incipient engine faults. We preprocess the data into $300$-timestep segments of $8$ principal components and establish an initial benchmark using nine diverse one-class anomaly detection models. Our experiments reveal significant performance variability across the vehicle fleet, underscoring the challenge of cross-vehicle generalization. Furthermore, our findings corroborate recent literature, showing that simple classical methods (e.g., K-Means and One-Class SVM) are often highly competitive with, or superior to, deep learning approaches in this segment-based evaluation. By publicly releasing EngineAD, we aim to provide a realistic, challenging resource for developing robust and field-deployable anomaly detection and anomaly prediction solutions for the automotive industry.

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