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

arXiv: https://arxiv.org/abs/2508.03730 · HTML: https://mlsanity.com/paper/2508.03730/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 41 references that are in the map.
- First posted on arXiv 30 Jul 2025.

## Builds on (most cited first, 6 of 6)

- [NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles](https://mlsanity.com/paper/2106.11810/) (2021)
- [One-Pass Trajectory Simplification Using the Synchronous Euclidean Distance](https://mlsanity.com/paper/1801.05360/) (2018)
- [PRESS: A Novel Framework of Trajectory Compression in Road Networks](https://mlsanity.com/paper/1402.1546/) (2014)
- [Bounded Quadrant System: Error-bounded Trajectory Compression on the Go](https://mlsanity.com/paper/1412.0321/) (2014)
- [Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets](https://mlsanity.com/paper/1502.05113/) (2015)
- [One-Pass Error Bounded Trajectory Simplification](https://mlsanity.com/paper/1702.05597/) (2017)

## Abstract (arXiv)

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.