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An Indoor Positioning Method for Micro Intelligent Vehicles

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Abstract

The paper deals with the positioning problem of Micro Intelligent Vehicles (MicroIVs) in Intelligent Transportation Simulation Platforms (ITSPs). We present a practical positioning solution, in which the absolute position data and the relative position data of each MicroIV are fused together via a Kalman filter and an assisted update algorithm. Precisely, each MicroIV gets its absolute position data through an equipped Radio Frequency Identification (RFID) reader which reads the RFID passive tags embedded in the platform. Meanwhile, a Dead Reckoning (DR) method is adopted to calculate the relative position of MicroIV. Then the Kalman filter is designed to fuse the absolute and relative position data. In addition, to compensate occasional RFID reading missing, the assisted update algorithm of the absolute position data is proposed. Experimental evaluation validates the effectiveness of the method.

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Acknowledgments

This work is supported by NSF of China (61273006), High Technology Research and Development Program of China (863 Program) (2011AA110301), Specialized Research Fund for the Doctoral Program of Higher Education of China (20111103110017).

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Authors and Affiliations

  1. Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, People’s Republic of China

    Dong Tong, Yangzhou Chen, Xiaojun Qu & Guiping Dai

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  1. Dong Tong
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  2. Yangzhou Chen
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  3. Xiaojun Qu
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  4. Guiping Dai
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Correspondence to Yangzhou Chen.

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Tong, D., Chen, Y., Qu, X. et al. An Indoor Positioning Method for Micro Intelligent Vehicles. Int. J. ITS Res. 15, 1–6 (2017). https://doi.org/10.1007/s13177-015-0114-7

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