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A Stake-Out Prototype System Based on GNSS-RTK Technology for Implementing Accurate Vehicle Reliability and Performance Tests

Author

Listed:
  • Paolo Visconti

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Francesco Iaia

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Roberto De Fazio

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Nicola Ivan Giannoccaro

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

Abstract

There are many car tests regulated by European and international standards and carried out on tracks to assess vehicle performance. The test preparation phase usually consists of placing road cones on the track with a specific configuration defined by the considered standard; this phase is performed by human operators using imprecise and slow methods, mainly due to the large required distances. In this paper, a new geolocation stake-out system based on GNSS RTK technology was realized and tested, supported by a Matlab-based software application to allow the user to quickly and precisely locate the on-track points on which to position the road cones. The realized stake-out system, innovative and very simple to use, produced negligible average errors (i.e., 2.4–2.9 cm) on the distance between the staked-out points according to the reference standards (distance percentage error 0.29–0.47%). Furthermore, the measured average angular error was also found to be very low, in the range 0.04–0.18°. Finally, ISO 3888-1 and ISO 3888-2 test configurations were reproduced on the proving ground of the Porsche Technical Center by utilizing the realized stake-out system to perform a double lane-change maneuver on car prototypes.

Suggested Citation

  • Paolo Visconti & Francesco Iaia & Roberto De Fazio & Nicola Ivan Giannoccaro, 2021. "A Stake-Out Prototype System Based on GNSS-RTK Technology for Implementing Accurate Vehicle Reliability and Performance Tests," Energies, MDPI, vol. 14(16), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4885-:d:611772
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    References listed on IDEAS

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    1. Andrius Kulsinskas & Petar Durdevic & Daniel Ortiz-Arroyo, 2021. "Internal Wind Turbine Blade Inspections Using UAVs: Analysis and Design Issues," Energies, MDPI, vol. 14(2), pages 1-19, January.
    2. Bowen Liu & Xiaojun Duan & Liang Yan, 2018. "A Novel Bayesian Method for Calculating Circular Error Probability with Systematic-Biased Prior Information," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, July.
    3. Roberto de Fazio & Donato Cafagna & Giorgio Marcuccio & Paolo Visconti, 2020. "Limitations and Characterization of Energy Storage Devices for Harvesting Applications," Energies, MDPI, vol. 13(4), pages 1-18, February.
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    Cited by:

    1. Andrzej Stateczny & Cezary Specht & Mariusz Specht & David Brčić & Alen Jugović & Szymon Widźgowski & Marta Wiśniewska & Oktawia Lewicka, 2021. "Study on the Positioning Accuracy of GNSS/INS Systems Supported by DGPS and RTK Receivers for Hydrographic Surveys," Energies, MDPI, vol. 14(21), pages 1-19, November.
    2. Mariusz Specht & Cezary Specht & Andrzej Stateczny & Paweł Burdziakowski & Paweł Dąbrowski & Oktawia Lewicka, 2022. "Study on the Positioning Accuracy of the GNSS/INS System Supported by the RTK Receiver for Railway Measurements," Energies, MDPI, vol. 15(11), pages 1-17, June.

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