Vehicle Sharing Route Optimization via Location Matching
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Solution Overview
Problem
Existing methods for sharing pay vehicles, such as taxis, face challenges in efficiently matching users with similar destinations, leading to higher fares and difficulties in selecting optimal routes for shared travel.
Innovation Solution
A vehicle sharing assisting apparatus that acquires and transmits optimal routes and vehicle information to user terminals, utilizing location information from both users and vehicles to facilitate efficient sharing, while also managing user interactions and vehicle dispatch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a vehicle dispatch center recognizes user locations and destinations to judge whether vehicles can be shared, then vehicle sharing can be facilitated, but it becomes impossible to share vehicles when no other user has the same location or destination
Solution Approach 1:
The system changes the parameter of destination matching from exact match to flexible range-based match. By allowing users to select a range around their destination and matching users whose destinations fall within this range, the system enables vehicle sharing even when destinations are not identical, thereby increasing the success rate of vehicle sharing while maintaining adaptability.
2Ease of operation
If users manually determine routes for shared vehicles, then routing flexibility is achieved, but users cannot efficiently select optimal routes without knowing who is located closest to vehicles
Solution Approach 1:
The system implements self-service by automatically calculating and providing optimal routes based on user locations, vehicle locations, and destinations. The route acquisition unit automatically determines the most efficient route that passes through relevant user locations, eliminating the need for manual route planning by users while minimizing time loss through automated optimization.
Solution Approach 2:
The system uses feedback from location information of users and vehicles to dynamically determine optimal routes. By continuously acquiring location data and using it to calculate the best route that minimizes travel time and distance, the system provides real-time route optimization that adapts to current conditions, reducing both operational complexity and time loss.
3Productivity
If the system extracts users with same locations and destinations for vehicle sharing, then sharing efficiency is improved, but the system complexity increases due to multiple judgment criteria
Solution Approach 1:
The system extracts only the essential elements needed for vehicle sharing: user location, destination, and vehicle location. By focusing on these key parameters and using range-based matching instead of complex multi-criteria judgment, the system maintains high sharing efficiency while reducing dispatch center complexity. The extraction of users within a threshold range simplifies the matching process compared to evaluating multiple detailed criteria.
Data Source
AI summary
An apparatus includes at least one processor and a transceiver. The at least one processor is configured to execute computer readable instructions to: acquire first location information representing locations of a plurality of user terminals, second location information representing a location of at least one vehicle, and third location information representing a location of a destination of the plurality of user terminals; and determine a route from the location of the at least one vehicle to the location of the destination based on the first location information, the second location information and the third location information, wherein the route includes the location of each of the plurality of user terminals. The transceiver is configured to transmit the route to the plurality of user terminals.