Weighted Parking Space Selection With User Exchange Incentives
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Solution Overview
Problem
Parking in densely populated urban environments is frustrating and time-consuming, with traditional systems requiring manual searches and cancellations for better spaces, and there's a need for efficient, automated methods to secure higher-value parking options.
Innovation Solution
A system that uses weighted parameter comparison to identify and automatically reserve parking spaces based on user preferences, dynamically adjusting parameters using machine learning, and facilitating exchanges between users to optimize parking reservations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual search systems are used for parking, then users can search for parking spaces, but the process is time-consuming and requires multiple cancellations and manual interventions
Solution Approach 1:
The system performs preliminary actions by automatically securing parking spaces based on predicted arrival times and listing values before users need to arrive. The server proactively reserves spaces and notifies users, eliminating the need for last-minute manual searches and cancellations.
Solution Approach 2:
The system enables self-service by automatically comparing listing values, determining optimal parking spaces, and executing reservations without requiring user intervention. The automated comparison of weighted parameters and automatic reservation system eliminates manual search and cancellation processes.
2Productivity
If automated systems secure parking spaces automatically, then parking efficiency improves, but users may not have control over their specific parking preferences
Solution Approach 1:
The system changes parameters by using weighted parameters that can be dynamically adjusted. Users can modify the weights of different criteria (proximity, price, availability) to reflect their personal preferences, and the system automatically re-evaluates based on these adjusted parameters, combining automation with user-specific control.
Solution Approach 2:
The system provides feedback by notifying users of secured parking spaces and allowing them to review and modify their preferences. The automated system compares current listings against user preferences and communicates results, enabling users to maintain control while benefiting from automation.
3Measurement precision
If the system compares multiple parking listings with different parameters, then better parking options are found, but the complexity of the selection process increases
Solution Approach 1:
The system simplifies complexity by transforming multiple parameters into a single listing value through weighted comparison. Instead of manually evaluating multiple criteria, the system converts them into a unified score that automatically identifies the best parking spaces, reducing perceived complexity while maintaining evaluation precision.
Solution Approach 2:
The system segments the complex evaluation process into independent weighted parameters (proximity, price, availability, etc.), each evaluated separately and then combined through a standardized comparison algorithm. This segmentation makes the complex multi-parameter evaluation manageable and systematic.
4Loss of time
If parking spaces are secured in advance, then users save time during peak periods, but available spaces may be limited and competition increases
Solution Approach 1:
The system addresses limited availability by performing preliminary reservation actions before peak periods. The server proactively secures parking spaces in advance based on predicted demand and listing values, ensuring spaces are reserved before they become unavailable during peak times.
Solution Approach 2:
The system handles dynamic availability by continuously monitoring and updating listing statuses. The automated comparison system adapts to changing availability conditions in real-time, allowing users to secure spaces when available while automatically adjusting to new conditions as spaces become occupied or released.
Data Source
AI summary
Parking space selection and navigation systems and methods are disclosed. Computing devices are configured to receive a search request from a user device to secure a first parking space, secure a first parking space for the first user device, determine a first value associated with the first parking space and a second value associated with a second parking space based on listing parameters, determine that the second value is greater than the first value by a predefined amount, and, in response to that determination, transmit a message to the user device comprising a prompt configured to secure the second listing and transmitting a second user-selectable message to a second user device, the second user-selectable message comprising a prompt configured to exchange the second parking space with the first with an incentive for the second user device to exchange parking spaces.