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Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
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An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services.
Yoonsik Bang1, Jiyoung Kim2, Kiyun Yu3
1Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea. bangys1004@snu.ac.kr.
Sensors (Basel, Switzerland)
|October 27, 2016
Summary
This study introduces a novel map-matching method for pedestrian navigation services, improving Global Positioning System (GPS) accuracy. The new Fréchet distance-based approach enhances pedestrian tracking by adapting to GPS errors and providing reliable location matching.
Area of Science:
- Computer Science
- Geographic Information Systems
- Mobile Computing
Background:
- Pedestrian Navigation Services (PNS) are increasingly reliant on accurate location data from wearable and smartphone technologies.
- Existing map-matching techniques, primarily developed for vehicles, are unsuitable for pedestrians due to distinct movement patterns and complex pedestrian map data.
- Accurate projection of Global Positioning System (GPS) trajectories onto road networks is crucial for effective PNS.
Purpose of the Study:
- To propose and evaluate a novel map-matching method specifically designed for pedestrian GPS trajectories.
- To address the limitations of vehicle-centric map-matching algorithms in the context of pedestrian navigation.
- To enhance the accuracy and reliability of pedestrian location tracking in PNS.
Main Methods:
- Developed a new map-matching method based on the Fréchet distance, a measure of geometric similarity between curves.
- Incorporated an adaptation coefficient to adjust the search range based on the auto-correlation of consecutive GPS points, mitigating positional errors.
- Implemented a real-time reliability index to evaluate and reduce matching errors.
Main Results:
- The proposed Fréchet distance-based map-matching method demonstrated superior performance compared to conventional vehicle-based techniques.
- The adaptive approach effectively handled positional errors inherent in GPS signals for pedestrian trajectories.
- Real-time reliability index evaluation contributed to more accurate and dependable map-matching outcomes.
Conclusions:
- The novel map-matching method offers a significant improvement for pedestrian navigation services by accurately projecting GPS data onto road networks.
- The approach effectively addresses the unique challenges of pedestrian movement and GPS signal variability.
- This research provides a more robust solution for enhancing the accuracy and reliability of pedestrian tracking systems.
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