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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(5): 227-236
TAO Wei-jie, CAI Bo-gen, LIU Jiang, WANG Jian, SHANGGUAN Wei. UKF-based three-dimensional track generation method for digital track map[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 227-236. doi: 10.19818/j.cnki.1671-1637.2020.05.019
Citation: TAO Wei-jie, CAI Bo-gen, LIU Jiang, WANG Jian, SHANGGUAN Wei. UKF-based three-dimensional track generation method for digital track map[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 227-236. doi: 10.19818/j.cnki.1671-1637.2020.05.019
shu

UKF-based three-dimensional track generation method for digital track map

doi: 10.19818/j.cnki.1671-1637.2020.05.019
  • 1.

    School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

  • 2.

    Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transportation, Beijing Jiaotong University, Beijing 100044, China

  • 3.

    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China

Funds:

National Key Research and Development Program of China 2016YFB1201500

National Natural Science Foundation of China 61873023

Fundamental Research Funds for the Central Universities 2018YJS016

Beijing Natural Science Foundation 4182053

More Information
    Abstract
  • To meet the requirements of digital track maps for the satellite-navigation-system-based train positioning, an unscented Kalman filter(UKF)-based track estimation method was proposed and a three-dimensional digital track map for railway tracks was generated. For the three basic curve elements(straight line, transition curve, and circular arc) in the horizontal profile of railway track, a mileage-parameterized Fresnel integral model was used for a unified modeling. For the straight line and curve in the vertical profile, a quadratic curve model was used for modeling. The states(mileage, three-dimensional coordinates) and parameters(heading, curvature, curvature rate, slope, and slope rate) of models were jointly estimated using the UKF. The normalized innovation squared and estimated distance error were introduced as the criteria to segment the track. The three-dimensional railway track was generated using the breakpoints along with the geometric parameters. The discrete point, cubic polynomial, and proposed Fresnel integral methods were compared by using the simulated horizontal track data. The Fresnel method was verified by using the 14.7 km field data from the Qinghai-Tibet Railway Line. Simulation result shows that the mean horizontal distance errors are below 0.024 m for all three methods under the same error requirement. However, the Fresnel method uses the fewest break points, with a data reduction rate of 99.76%. In addition, the maximum chainage error of Fresnel method is the smallest, which decreases from 0.964 m to only 0.060 m, with a reduction of 93.77%. The heading and curvature of Fresnel method are considerably more accurate than those of the cubic polynomial method, which are closer to the true value. The field data test results demonstrate that the Fresnel method can use 22 and 20 break points with their parameters to generate the horizontal and vertical curves, respectively. The mean distance errors of horizontal and vertical curves are below 0.03 m, while the maximum accumulative mileage error is only 0.078 m, which indicates high accuracies of both position and geometry.

     

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