Abstract

A train positioning method based on GPS and digital rail line matching is proposed. Firstly, the digital track line is generated based on the fitting and interpolation algorithm of train track line. And then the GPS data are corrected by the track line positioning correction method, and the more accurate position estimation of the train is obtained. Finally, the data track line is simulated and analyzed with some measured data from Harbin to Qigihar track line. The analysis results show that cubic spline curve is better than cubic B-spline curve on the establishment of digital track map.

Highlights

  • The railway transportation has the characteristics of strong transportation capacity, fast speed, wide network coverage, and so on

  • Through the analysis and calculation of the simulation, we can see that fitting and interpolation can basically approximate the railway track. Whether it is fitting or interpolation, the cubic spline is more in line with the actual trajectory

  • The safety of GPS plays an important role in improving the safety and capacity of railway transportation system, as well as effectively managing the transportation of railway high value-added freight

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Summary

Introduction

The railway transportation has the characteristics of strong transportation capacity, fast speed, wide network coverage, and so on. The main implementation methods include track circuit positioning, response inquiry, train positioning, cross induction loop positioning, speed measurement and positioning, etc. These methods have limitations [1]. As a kind of global satellite navigation system, GPS can be used for all-weather and continuous train positioning. It has the advantages of high real-time positioning accuracy, low cost, small size, convenient maintenance and so on. The research on train positioning method based on GPS is of great significance to promote the development of railway transportation

Analysis of Problems
Digital Track Map
Fitting Method of Track Line
Interpolation Method of Track Line
Map Matching Method
Projection Correction Method
Average Distance Method
Grid Matching Method
Simulation and Analysis
Summary and Conclusions
Full Text
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