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Area of Science:

  • Embedded Systems Engineering
  • Signal Processing
  • Automotive Technology

Background:

  • Efficient computing resource operation is crucial for microprocessor-embedded systems.
  • Real-time data processing enhances system performance, particularly in vehicle speed measurement.
  • Minimizing computation time for speed evaluation is a key objective.

Purpose of the Study:

  • To evaluate and compare four computational methods for vehicle speed measurement.
  • To analyze the reliability and performance of these methods under varying conditions.
  • To identify the most efficient method for real-time embedded systems.

Main Methods:

  • Analysis of four computational methods, including cross-correlation.
  • Processing of magnetic field magnitude signals from 200 vehicles.
  • Comparison of sample delay values and program execution times.

Main Results:

  • Evaluated speed and program execution times were recorded for each method.
  • Cross-correlation methods showed limitations with small sample sizes.
  • The reliability of cross-correlation was questioned for specific signal segments.

Conclusions:

  • The choice of computational method significantly impacts vehicle speed measurement accuracy and efficiency.
  • Cross-correlation methods may not be universally optimal, especially for limited data segments.
  • Further research into robust algorithms for real-time embedded speed measurement is warranted.