Rental Vehicle Search Clustering for Processing Limits
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Computer systems used by vehicle rental providers have limited processing power, leading to an inability to communicate all available rental options to users, particularly in large cities, resulting in incomplete geographical coverage and higher rental rates being overlooked.
Innovation Solution
A system that clusters available rental stores by geographical position, selects a subset of stores within each cluster, and queries rental provider systems for rate and availability information, allowing for the ranking of vehicles based on specific characteristics and rental rates, while managing message size to accommodate processing limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system queries all rental stores in a city, then the completeness of rental options is improved, but the processing load on rental provider computer systems increases
Solution Approach 1:
The patent divides the city into multiple geographical clusters, each containing a subset of rental stores. Instead of querying all stores uniformly, the system segments the search space and queries a limited number of stores from each cluster, reducing the total number of queries while maintaining comprehensive coverage across different city regions.
2Area of stationary object
If the system increases the number of rental stores queried, then the geographical coverage is improved, but the message size and processing time increase
Solution Approach 1:
The system segments the city into geographical clusters and processes a limited number of stores from each cluster. This segmentation allows the system to achieve broad geographical coverage without processing every single store in the city, thereby reducing overall processing time while maintaining comprehensive spatial coverage.
3Productivity
If the system uses alphabetical coding to select rental locations, then the processing efficiency is improved, but the geographical coverage and price competitiveness deteriorate
Solution Approach 1:
Instead of using alphabetical coding that prioritizes certain locations regardless of geography, the system inverts the approach by using geographical clustering. This ensures that selection is based on spatial distribution and price competitiveness rather than arbitrary alphabetical order, maintaining both efficiency and comprehensive coverage.
4Productivity
If the system reduces the number of rental stores queried, then the processing load is reduced, but the rental options communicated to users become limited
Solution Approach 1:
The system segments the city into multiple geographical clusters and queries a representative number of stores from each cluster. This ensures that even with a reduced total number of queries, users still receive diverse vehicle options from different geographical areas, maintaining adaptability and vehicle choice while reducing processing load.
Data Source
AI summary
Methods, systems, and computer program products for providing available rental vehicle options to a user. The system includes a network interface with at least one rental provider computer system. The system receives a rental request for an available rental vehicle. The rental request includes a pick-up location and a drop-off location. In response to receiving the rental request, the system queries a rental store database for a plurality of available rental stores in both the pick-up location and the drop-off location. The system arranges the available rental stores into at least one cluster in the pick-up location and the drop-off location based on a geographical position of the available rental stores. The system selects a particular number of available rental stores within each cluster in both the pick-up location and the drop-off location.