提升投票式轨迹匹配效率，适应不同采样率与缺失数据。
Enhancing Interactive Voting-Based Map Matching: Improving Efficiency and Robustness for Heterogeneous GPS Trajectories
- 引入距离约束投票机制，降低计算开销。
- 结合轨迹补全与路网缺失处理，提升鲁棒性。
- 适配OpenStreetMap，支持全球任意区域应用。
本文提出一种增强版交互投票式地图匹配算法，旨在高效处理采样率各异的轨迹数据，实现高精度轨迹重建且不受输入质量影响。在原有仅用于将GPS信号对齐至道路网络的基础上，新增轨迹插值功能，并采用距离有界交互投票策略以减少计算复杂度，同时改进了对道路网络缺失数据的处理。此外，集成基于OpenStreetMap构建的自定义地理资产，使该方法可无缝应用于覆盖于OpenStreetMap道路网络的任何地理区域。这些改进在保持原算法核心优势的同时，显著拓展其在多样化真实场景中的适用性。
原文摘要 · Abstract (English)
This paper presents an enhanced version of the Interactive Voting-Based Map Matching algorithm, designed to efficiently process trajectories with varying sampling rates. The main aim is to reconstruct GPS trajectories with high accuracy, independent of input data quality. Building upon the original algorithm, developed exclusively for aligning GPS signals to road networks, we extend its capabilities by integrating trajectory imputation. Our improvements also include the implementation of a distance-bounded interactive voting strategy to reduce computational complexity, as well as modifications to address missing data in the road network. Furthermore, we incorporate a custom-built asset derived from OpenStreetMap, enabling this approach to be smoothly applied in any geographic region covered by OpenStreetMap's road network. These advancements preserve the core strengths of the original algorithm while significantly extending its applicability to diverse real-world scenarios.
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