tracematch

High-performance GPS route matching library for fitness applications.

Features

• AMD Route Matching - Average Minimum Distance for robust polyline similarity
• Bidirectional Detection - Detects forward and reverse route matches
• R-tree Spatial Indexing - O(log n) pre-filtering for batch operations
• Section Detection - Multi-scale detection of frequently-traveled sections
• Parallel Processing - Rayon-based parallel grouping
• Mobile FFI - UniFFI bindings for iOS and Android

Installation

[dependencies]
tracematch = "0.1"

Quick Start

use tracematch::{GpsPoint, RouteSignature, MatchConfig, compare_routes};

let route = vec![
    GpsPoint::new(51.5074, -0.1278),
    GpsPoint::new(51.5080, -0.1290),
    GpsPoint::new(51.5090, -0.1300),
];

let config = MatchConfig::default();
let sig1 = RouteSignature::from_points("route-1", &route, &config);
let sig2 = RouteSignature::from_points("route-2", &route, &config);

if let (Some(s1), Some(s2)) = (sig1, sig2) {
    if let Some(result) = compare_routes(&s1, &s2, &config) {
        println!("Match: {}% ({})", result.match_percentage, result.direction);
    }
}

References

Section detection:

• TRACLUS (Lee, Han, Whang, SIGMOD 2007) - MDL-based trajectory partitioning (paper)
• TS-MF (Xu et al., 2022) - Trajectory segmentation and mergence (paper)
• Graph-based trajectory clustering (Hwang et al., 2013) - Network-constrained clustering (paper)
• GPS segment averaging (MDPI 2019) - Consensus polyline computation (paper)

Foundational algorithms:

• R*-tree (Beckmann et al., SIGMOD 1990) - Spatial indexing (paper)
• Union-Find (Tarjan, 1975) - Disjoint set clustering (paper)
• Douglas-Peucker (Douglas & Peucker, 1973) - Line simplification (paper)
• Medoid/k-medoids (Kaufman & Rousseeuw, 1987) - Representative selection
• Haversine formula - Great-circle distance (Wikipedia)

License

Apache-2.0