Distinguishing Level 0 and Level 2 driving mode via spectral analysis of lateral position: Insights from a highway Naturalistic Driving Study

Abstract

The development of Level 2 driving systems complicates the interpretation of Naturalistic Driving Study (NDS) data, as behavioral modeling requires accurate identification of the operational mode. While longitudinal control has already been studied, lateral behavior remains underexplored, particularly in the frequency domain. This study proposes a classification framework to distinguish between SAE Level 0 and Level 2 driving using the Power Spectral Density (PSD) of the vehicle's lateral position. High-precision trajectory data (10 Hz) from six instrumented vehicles were collected on the I-24 MOTION testbed, and the signals were split into short driving episodes. We extract five spectral metrics, band power, slope, centroid, band power ratio, and entropy, to capture distinct control signatures. Statistical analysis confirms significant differences between driving modes across all examined time horizons (15-90 s). A logistic regression model achieves a peak accuracy of 92% at a 60-second observation window, identifying this as the optimal duration. These results demonstrate that frequency-domain methods effectively separate machine control from human steering, providing a foundational tool for large-scale safety analysis and automated dataset labeling.