PILOT-C: Physics-Informed Low-Distortion Optimal Trajectory Compression

TL;DR

PILOT-C is a physics-informed trajectory compression framework that significantly improves compression ratios and error reduction for 2D and 3D trajectories, outperforming existing methods while supporting arbitrary dimensions.

Contribution

It introduces a novel physics-based, error-bounded compression method that extends line simplification to arbitrary dimensions, including 3D, with superior performance.

Findings

Outperforms CISED-W by 19.2% in compression ratio.

Reduces trajectory error by 32.6% on average.

Achieves 49% better compression in 3D compared to SQUISH-E.

Abstract

Location-aware devices continuously generate massive volumes of trajectory data, creating demand for efficient compression. Line simplification is a common solution but typically assumes 2D trajectories and ignores time synchronization and motion continuity. We propose PILOT-C, a novel trajectory compression framework that integrates frequency-domain physics modeling with error-bounded optimization. Unlike existing line simplification methods, PILOT-C supports trajectories in arbitrary dimensions, including 3D, by compressing each spatial axis independently. Evaluated on four real-world datasets, PILOT-C achieves superior performance across multiple dimensions. In terms of compression ratio, PILOT-C outperforms CISED-W, the current state-of-the-art SED-based line simplification algorithm, by an average of 19.2%. For trajectory fidelity, PILOT-C achieves an average of 32.6% reduction in error compared to CISED-W. Additionally, PILOT-C seamlessly extends to three-dimensional trajectories while maintaining the same computational complexity, achieving a 49% improvement in compression ratios over SQUISH-E, the most efficient line simplification algorithm on 3D datasets.