Parking Facility Pricing Data Structure
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Solution Overview
Problem
Existing parking facility pricing systems rely on coarse pricing bands that do not accurately reflect hourly or minute-to-minute demand and fail to account for external factors like weather, leading to inefficient revenue capture and high computational costs for dynamic pricing systems.
Innovation Solution
A data structure comprising an array of cells defined by time of entry and parking duration, where each cell stores a cost, allowing for the efficient calculation of parking session costs by summing relevant cells, reducing computational overhead and enabling granular pricing based on occupancy rates, weather, and events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If coarse pricing bands are used to simplify rate structure, then ease of operation is improved, but measurement precision of parking demand is worsened
Solution Approach 1:
The patent segments the pricing structure into multiple granular pricing bands based on time of day, day of week, and event types. Instead of using coarse single-rate structures, the system divides parking rates into numerous specific bands (e.g., off-peak hours, peak hours, weekend rates, event premium rates), allowing precise reflection of demand variations while maintaining operational simplicity through automated rate application.
2Measurement precision
If dynamic pricing systems are implemented to reflect real-time demand, then measurement precision of parking demand is improved, but use of energy by moving object is worsened
Solution Approach 1:
The patent pre-calculates and stores pricing rates for multiple scenarios in advance (off-peak rates, peak rates, event rates) rather than computing prices in real-time based on current demand. This preliminary action approach allows the system to respond quickly to parking transactions without performing energy-intensive real-time demand modeling, thus maintaining measurement precision while reducing computational energy consumption.
3Productivity
If traditional dynamic pricing systems are used to capture revenue, then revenue capture is improved, but device complexity is worsened
Solution Approach 1:
The patent changes the parameters used for pricing from continuous real-time demand modeling to discrete predefined rate categories. By transforming the pricing approach into parameter-based lookup (selecting from predefined rate tables based on time and event conditions), the system achieves effective revenue capture without the complexity of continuous optimization algorithms and real-time predictive modeling.
4Measurement precision
If granular pricing bands are implemented to reflect minute-to-minute demand, then measurement precision is improved, but device complexity is worsened
Solution Approach 1:
The patent creates simplified copies of complex pricing scenarios in the form of predefined rate tables and lookup structures. Instead of implementing complex real-time demand calculation algorithms, the system uses simplified copied representations of pricing scenarios (off-peak, peak, event rates) that can be quickly applied to transactions. This copying approach maintains measurement precision through comprehensive rate coverage while reducing device complexity through straightforward data structure implementation.
Data Source
AI summary
A method for operating a parking facility includes accessing a data structure comprising an array of cells defined by a plurality of columns and a plurality of rows, wherein one of the plurality of columns and the plurality of rows is time of entry and the other of the plurality of columns and the plurality of rows is duration of parking session, and each cell of the array of cells comprises a cost, and determining a parking session cost for an individual vehicle by summing costs in a plurality of cells of the array of cells corresponding to a time of entry and a parking session duration for the individual vehicle.