Carpooling Service Time Recommendation System
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Solution Overview
Problem
Existing online carpooling services face inefficiencies due to dispersed start times of service requesters, making successful carpooling less efficient.
Innovation Solution
A system and method that determine recommended start times for passengers based on historical orders, route similarity, and estimated driving times, allowing passengers to select optimal times for carpooling, thereby improving the chances of successful carpooling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If passengers choose any time in a day as their start time, then flexibility is improved, but carpooling efficiency deteriorates due to dispersed start times
Solution Approach 1:
The system changes the time parameter by determining recommended start times based on historical order data, route similarity, and estimated driving times. This transforms the random time selection into an optimized time selection process, aligning multiple passengers' start times to improve carpooling efficiency while maintaining flexibility through multiple recommended time options.
Solution Approach 2:
The system uses historical order data as feedback to determine recommended start times. By analyzing past carpooling patterns and using this information to guide future time selections, the system improves carpooling efficiency without sacrificing passenger flexibility.
2Productivity
If the system determines recommended start times based on multiple factors, then carpooling efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments the complexity by dividing the recommended time determination into distinct modules: historical order analysis, route similarity calculation, and estimated driving time computation. Each module handles a specific aspect of the problem, making the overall system more manageable while achieving high carpooling efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-calculating historical order data, route similarities, and driving time estimates before determining the final recommended start time. This preparation work is done in advance to streamline the decision-making process and reduce real-time computational complexity.
Data Source
AI summary
Systems and methods for reserving a carpooling service are provided. A method may include: obtaining, from a first passenger terminal, a first service request including a first start location and a first destination; determining at least one first recommended time based on the first start location and the first destination; obtaining a first start time from the first passenger terminal, the first start time is selected from the at least one first recommended time by the first passenger terminal; obtaining, from a second passenger terminal, a second service request including a second start location and a second destination after the obtaining of the first service request; and determining a second recommended time for the second passenger terminal based on the first start location, the second start location, and the first start time.