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Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Real Track Experiment Dataset for Motorcycle Rider Behavior and Trajectory Reconstruction.

Bastien Vincke1, Pauline Michel1, Abdelhafid El Ouardi1

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|November 11, 2024
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This study analyzes motorcycle rider and vehicle dynamics during cornering. Researchers collected precise trajectory data using multi-sensor instrumentation on a racetrack to understand rider-machine interactions.

Keywords:
Embedded multisensor systemMotorcycle instrumentationRider behaviorSensors data synchronization

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Area of Science:

  • Vehicle Dynamics and Control
  • Robotics and Autonomous Systems
  • Human-Machine Interaction

Background:

  • Motorcycle dynamics, especially during cornering, are complex and under-researched compared to cars due to rider variability and lower vehicle fleet representation.
  • Understanding motorcycle trajectories is crucial for developing advanced rider assistance systems and improving safety.

Purpose of the Study:

  • To analyze the complex interactions between a motorcycle rider and their vehicle during the bend-taking maneuver.
  • To study and reconstruct the precise trajectory of a motorcycle using advanced sensor data.

Main Methods:

  • Multi-sensor instrumentation of a Honda CBF1000 motorcycle, including RTK GPS receivers for ground truth.
  • Data collection through real-world experiments conducted on the "La Ferté Gaucher" racetrack.
  • Validation of sensor data consistency and measurement relevance for trajectory analysis.

Main Results:

  • The study established a consistent dataset for analyzing motorcycle dynamics and rider interactions.
  • Preliminary analysis confirmed the relevance of the embedded sensors for precise trajectory reconstruction.
  • The collected data provides a foundation for future research into motorcycle control and rider behavior.

Conclusions:

  • The developed methodology enables detailed analysis of motorcycle rider-vehicle dynamics during cornering.
  • The validated dataset and sensor suite are suitable for studying precise motorcycle trajectories and rider interactions.
  • This research contributes to a better understanding of two-wheeled vehicle control and maneuverability.