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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Perception, Positioning and Decision-Making Algorithms Adaptation for an Autonomous Valet Parking System Based on

Felipe Jiménez1, Miguel Clavijo1, Alejandro Cerrato1

  • 1University Institute for Automobile Research (INSIA), Campus Sur UPM, Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain.

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Summary
This summary is machine-generated.

Autonomous vehicles can now find and park in spaces using only a LiDAR sensor. This system integrates perception, positioning, and control for efficient autonomous parking without infrastructure support.

Keywords:
LiDARautonomous vehicleparking maneuvervalet parking

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Autonomous parking valet systems enhance user convenience by automating parking searches and maneuvers.
  • Existing systems often rely on complex infrastructure or multiple sensors.
  • Challenges remain in achieving reliable autonomous parking with minimal sensing.

Purpose of the Study:

  • To integrate perception, positioning, decision-making, and maneuvering algorithms for autonomous vehicle control in parking lots.
  • To develop a system utilizing a single LiDAR sensor without additional infrastructure support.
  • To enable autonomous vehicles to autonomously search for and execute parking maneuvers.

Main Methods:

  • A simplified digital map was used to define the search range for parking spaces.
  • The autonomous vehicle employed a single LiDAR sensor for navigation and space detection.
  • Algorithms for perception, positioning, decision-making, and maneuvering were integrated.
  • Two alternative parking strategies were implemented to optimize space utilization.

Main Results:

  • The system successfully integrated perception, positioning, decision-making, and maneuvering algorithms.
  • Autonomous vehicles accurately located and maneuvered into parking spaces using only LiDAR.
  • The system demonstrated reliable performance in a real-world parking lot with canopies.

Conclusions:

  • A single LiDAR sensor is sufficient for robust autonomous parking in complex environments.
  • The developed algorithms enable efficient and accurate autonomous parking maneuvers.
  • This approach reduces reliance on external infrastructure, making autonomous parking more feasible.