Automated Valet Parking Testing

Automated Valet Parking (AVP) testing evaluates the functionality, reliability, and safety of a vehicle’s autonomous parking capabilities in controlled and real-world conditions. The process ensures that AVP systems meet technical, regulatory, and user expectations for seamless operation in diverse environments.

Key Objectives of AVP Testing

  1. Safety Validation: Ensures the system can park and retrieve the vehicle without causing collisions or endangering pedestrians.
  2. Accuracy: Verifies that the vehicle can navigate parking facilities and park in designated spots.
  3. Reliability: Tests consistent performance under varying conditions such as low lighting, tight spaces, or crowded lots.
  4. Infrastructure Integration: Confirms compatibility with parking facility technology, including sensors, cameras, and communication systems.

Components Tested in AVP Systems

  1. Sensor Performance: Radar, cameras, ultrasonics, and LiDAR are tested for obstacle detection, precision, and robustness in identifying other vehicles, pedestrians, and infrastructure elements.
  2. Vehicle-to-Infrastructure Communication (V2I): Ensures smooth communication between the car and smart parking systems to coordinate navigation and parking.
  3. Autonomous Navigation: Validates the system’s ability to:
    • Follow pre-mapped routes.
    • Avoid obstacles dynamically.
    • Adapt to unexpected situations (e.g., other moving cars, humans crossing).
  4. Parking Space Detection: Assesses the vehicle’s ability to locate and identify an appropriate parking spot, even in tight or irregular layouts.
  5. Pick-Up Process: Tests the system’s ability to navigate back to the designated pick-up point efficiently when summoned.

Testing Scenarios

  1. Static Environment Testing: Conducted in controlled parking facilities to simulate basic scenarios like empty lots, standard spaces, and predefined routes.
  2. Dynamic Environment Testing: Introduces moving elements like pedestrians, bicycles, or other vehicles to assess obstacle avoidance and decision-making.
  3. Complex Parking Structures: Evaluates performance in multi-level garages, angled spaces, or areas with narrow lanes and sharp turns.
  4. Edge Cases: Scenarios include:
    • Malfunctioning infrastructure components (e.g., broken sensors).
    • Unexpected changes like a parked vehicle blocking the route.
    • Poor environmental conditions (e.g., low light, rain, reflective surfaces).

Test Tools and Methods

  1. Simulation Platforms: Digital environments recreate real-world scenarios to test AVP systems without physical risk.
  2. Physical Test Tracks: Dedicated parking lots with programmable obstacles and lighting variations for real-world testing.
  3. Connected Infrastructure Testing: Evaluates compatibility and communication with smart parking systems using V2I protocols.
  4. Data Logging and Analysis: Captures vehicle behavior, sensor data, and decision-making to refine algorithms.