Autonomous Parking Node Tree Path Planner
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Solution Overview
Problem
Existing autonomous driver assistance systems for parking require operator intervention to locate and position the vehicle, limiting their ability to autonomously park or un-park without increasing costs, and lacking in accuracy, robustness, and safety features.
Innovation Solution
A method for autonomously parking or un-parking a vehicle by generating and following a path using a node tree path planner, which selects the lowest cost nodes based on distance and steering angle, while avoiding obstructed areas and previously generated nodes, utilizing sensors and vehicle control systems for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous parking systems require operator intervention to locate and position the vehicle, then the system complexity and cost are reduced, but the extent of automation and productivity are limited
Solution Approach 1:
The autonomous parking system is divided into distinct functional modules: sensor subsystem for environmental perception, communication subsystem for data exchange, controller for path planning and decision-making, and vehicle control system for execution. This segmentation allows each module to be independently optimized and managed, reducing overall system complexity while maintaining high automation capability.
Solution Approach 2:
The system performs preliminary actions by pre-mapping the parking area using sensors before the actual parking operation. The controller pre-calculates multiple potential paths and identifies the optimal route in advance, allowing the vehicle to execute the parking maneuver autonomously without requiring real-time operator intervention or complex on-the-fly decision-making.
2Productivity
If traditional parking assistance systems are used, then the ease of operation is maintained with operator control, but the productivity and time efficiency are reduced
Solution Approach 1:
The vehicle performs parking operations autonomously without continuous operator intervention. The sensor subsystem independently detects obstacles and environmental features, the controller automatically plans and adjusts the parking path, and the vehicle control system executes maneuvers without requiring the operator to manually steer or monitor every action, significantly improving productivity while maintaining ease of use through simple activation commands.
3Adaptability or versatility
If autonomous parking systems are implemented without leveraging preexisting infrastructure, then the adaptability to different environments is improved, but the device complexity and cost increase
Solution Approach 1:
The sensor subsystem is designed to detect and process multiple types of environmental features and obstacles using the same hardware components. The controller applies universal path-planning algorithms that can handle various parking lot layouts, obstacle configurations, and vehicle types without requiring specialized equipment or complex customizations, achieving high adaptability with moderate system complexity.
Data Source
AI summary
A method for autonomously parking or un-parking a motor vehicle includes the steps of locating the motor vehicle within a parking area, setting a destination location within the parking area, generating and setting a path from the location of the motor vehicle to the destination location, and autonomously driving the motor vehicle along the path. The path is generated by (a) generating a first set of nodes from the location of the motor vehicle, (b) assigning a cost to each node in the first set of nodes, (c) selecting a lowest cost node from the first set of nodes, (d) generating another set of nodes from the selected node, (e) assigning a cost to each of the newly generated nodes, (f) selecting a lowest cost node from all of the nodes, and (g) repeating steps (d)-(f) until a lowest cost node is located at the destination location.