Autonomous Parallel Parking Wheel Control on Graded Roads
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Solution Overview
Problem
Autonomous vehicles face challenges in performing safe parallel parking maneuvers on graded roads, as they need to adjust tire angles to prevent rolling into the roadway, a task that is complex for both human drivers and AVs, especially on uphill and downhill slopes.
Innovation Solution
The AV determines the road grade using map data or sensors like LiDAR and adjusts wheel angles to ensure proper tire rotation and contact with the curb, using a feedback and control system to maintain optimal wheel angles, which minimizes movement in case of parking or emergency brake failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AV adjusts wheel angles to prevent rolling on graded roads, then safety is improved, but the complexity of the parking maneuver increases
Solution Approach 1:
The system determines the road grade using map data or sensors before executing the parallel parking maneuver. By knowing the grade in advance, the navigation system can pre-calculate the appropriate wheel angles needed to prevent rolling, rather than adjusting wheels reactively during parking. This preliminary determination simplifies the overall maneuver complexity while ensuring safety.
Solution Approach 2:
The system uses a feedback and control system to monitor wheel angles and adjust them automatically during the parallel parking maneuver. Sensors detect the actual wheel position and provide feedback to the control system, which makes real-time adjustments to maintain the optimal wheel angles determined for the specific road grade. This closed-loop control ensures safety while automating the complex adjustments.
2Measurement precision
If the AV uses sensors like LiDAR to determine road grade, then measurement precision is improved, but the use of energy increases
Solution Approach 1:
The system utilizes map data that contains pre-stored road grade information for various locations. Instead of always using energy-intensive LiDAR sensors to determine road grade, the AV first checks whether grade information is available in the map database for its current location. This multi-source approach allows the system to use low-energy map data when sufficient, reserving sensor-based measurement for cases where map data is unavailable or insufficient.
3Reliability
If the AV maintains optimal wheel angles using feedback control, then reliability is improved, but the device complexity increases
Solution Approach 1:
The feedback and control system automatically monitors and adjusts the wheel angles during the parallel parking maneuver without requiring manual intervention. The system determines the optimal wheel angles based on the road grade and autonomously maintains these angles throughout the parking process, adjusting for any deviations automatically. This self-service capability ensures parking stability while the automation manages the control complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables autonomous vehicles to perform safe parallel parking maneuvers by determining road inclination and adjusting wheel direction, ensuring optimal contact with the curb and reducing the risk of rolling into the roadway, thus enhancing safety and efficiency in ride-sharing deployments.
Implementation Method 1
The AV determines the road grade using map data or sensors like LiDAR
Data Source
AI summary
The subject disclosure relates to features that improve safety for autonomous vehicle (AV) maneuvers and in particular, that improve safety for parallel parking. A process of the disclosed technology includes steps for initiating a parking maneuver, navigating the AV into a parking location, and detecting a roadway grade with respect to a direction of the AV. In some aspects, the process can further include steps for automatically adjusting a wheel angle of the AV based on the roadway grade with respect to the direction of the AV. Systems and machine-readable media are also provided.