Parking Spot Finder with Driver Skill Grading
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Solution Overview
Problem
Conventional parking spot finder systems bring drivers to the entrance of parking lots or garages rather than directly to an individual parking spot, resulting in wasted time, energy, and increased emissions as drivers search for suitable spots.
Innovation Solution
A computer-implemented method and system that receives map data upon entering a parking area, determines available spots, grades them based on difficulty, assesses the driver's skill level, and selects a suitable spot with potential financial incentives, providing visual guidance to the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional parking spot finder systems bring drivers to the entrance of parking lots or garages, then drivers can locate parking areas, but drivers spend significant time and energy searching for suitable spots, increasing emissions
Solution Approach 1:
The system segments the parking area into individual parking spots and grades them based on difficulty metrics (aisle width, curvature, obstacles). Instead of treating the entire parking lot as a single destination, the system divides it into manageable, evaluable units that can be individually assessed and guided to, enabling precise navigation to suitable spots rather than general area location.
Solution Approach 2:
The system performs preliminary grading of all parking spots before the driver arrives. Difficulty metrics such as aisle width, curvature, obstacles, and lighting conditions are pre-calculated and stored. When the driver enters the parking area, the system instantly matches the driver's skill level with pre-graded spots, eliminating the need for on-the-spot searching and decision-making.
2Object-generated harmful factors
If drivers search for suitable parking spots manually after entering the parking area, then drivers can find parking, but the vehicle generates significant emissions during the search process
Solution Approach 1:
The system provides real-time feedback to the driver by displaying the grade of upcoming parking spots through the display unit. As the driver approaches the parking area, the system continuously updates information about suitable spots based on the driver's skill level, allowing the driver to make informed decisions without exhaustive searching. This feedback loop reduces unnecessary driving and emissions.
Solution Approach 2:
The system enables the driver to self-select an appropriate parking spot based on their skill level and the system's recommendations. The driver maintains control over the final decision while benefiting from the system's analytical capabilities. This self-service approach reduces stress and allows for more efficient parking behavior, indirectly reducing emissions through optimized search patterns.
3Adaptability or versatility
If the system grades parking spots based on difficulty and matches them to driver skill level, then parking suitability is optimized, but the system complexity increases
Solution Approach 1:
The system uses parameter changes to represent parking spot characteristics (aisle width, curvature, obstacles) as numerical difficulty metrics. By converting physical characteristics into quantifiable parameters and grading them on a standardized scale, the system enables automated matching with driver skill levels. This parameterization approach simplifies the matching logic while maintaining high adaptability to different parking scenarios.
Solution Approach 2:
The system introduces an intermediary grading scale that mediates between the physical characteristics of parking spots and the driver's skill level. Rather than directly comparing complex physical attributes with subjective skill assessments, the system uses the difficulty grade as an intermediary metric. This intermediary layer simplifies the matching process while preserving the nuanced relationship between spot characteristics and driver capability.
Data Source
AI summary
Method and systems for selecting available parking spots based on a skill level of the driver and a grade of the available parking spots. Map data is received by a vehicle via a network upon entering a parking area. Available parking spots are determined based on the map data. The parking spots are graded by a parking spot identifier based in at least the difficulty to park in the parking spot. The skill level of the driver is also graded by the parking spot identifier. At least one parking spot is selected by the parking spot identifier from the available parking spots based on the skill level of the driver and the grade of the available parking spots. A determination is made if the at least one selected parking spot includes a financial incentive to park in the selected parking spot.