Related Experiment Video
Updated: Jun 13, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
A novel fuzzy system-based genetic algorithm for trajectory segment generation in urban global positioning system
Xiaojuan Ran1, Naret Suyaroj2, Worawit Tepsan2
1International College of Digital Innovation, Chiang Mai University, Chiang Mai 50200, Thailand; School of Information and Engineering, Sichuan Tourism University, Chengdu 610100, China.
This study introduces an enhanced Fuzzy System-based Genetic Algorithm (FGA) for automated urban trajectory generation using Global Positioning System (GPS) data. The FGA method optimizes clustering and trajectory reconstruction without manual intervention.
Area of Science:
- Geographic Information Science
- Computer Science
- Transportation Engineering
Background:
- Global Positioning System (GPS) data is crucial for urban planning and travel analysis.
- Traditional trajectory generation methods lack automation and optimality due to manual cluster number settings.
Purpose of the Study:
- To develop an automated trajectory segment generation method using an enhanced Fuzzy System-based Genetic Algorithm (FGA).
- To overcome limitations of manual cluster number settings in traditional trajectory generation.
Main Methods:
- Integration of a fuzzy system with a genetic algorithm to dynamically adjust parameters.
- Utilizing angle-based partitioning and cosine-constrained segmentation for sub-trajectory generation.
- Employing global search capability and least squares regression for trajectory reconstruction.
Main Results:
- The FGA method automatically determines optimal cluster numbers across various clustering algorithms (K-means, K-median, FCM).
- Achieved globally optimal, smooth trajectory representations with improved clustering quality, continuity, and stability.
- Demonstrated effectiveness in reconstructing real-world taxi GPS data.
Conclusions:
- The proposed FGA provides an effective and adaptive solution for urban GPS trajectory segment generation.
- Future research will focus on enhancing scalability, noise robustness, and rule generalization.
Related Concept Videos
Errors in Global Positioning System
Introduction to Global Positioning System
Types of Global Positioning System Surveys
Field Application of Global Positioning System
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device
Design Example: Alignment of a Road Line Using GIS

