Pooled Route Generation for Shared Vehicle Service Area Extension
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Solution Overview
Problem
Shared vehicle service providers are limited in extending their service area to accommodate destinations outside the designated service area, as users cannot travel to these locations using shared vehicles due to logistical and capacity constraints.
Innovation Solution
A computer-implemented method and system that computes a pooled route allowing a user to travel to a destination outside the service area using a shared vehicle, by matching the user with another user who can return the vehicle to the service area, based on proximity and time thresholds, thereby extending the service area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the service area is limited to designated areas for logistic and capacity reasons, then the operational control and vehicle management are simplified, but the user's ability to travel to destinations outside the service area is restricted
Solution Approach 1:
The service area boundary is made dynamic by allowing temporary extensions through pooled routes. The system dynamically adjusts the effective service area based on real-time matching of users with similar trip patterns, enabling the service boundary to expand flexibly without permanent infrastructure changes.
Solution Approach 2:
The shared vehicle serves multiple functions by enabling both traditional trips within the service area and extended trips outside the service area through pooled routing. The same vehicle pool handles both service area operations and extended destination trips, eliminating the need for separate vehicle fleets.
2Adaptability or versatility
If the service area is extended to support destinations outside the service area, then the user's travel flexibility is improved, but the logistical complexity and capacity management become more difficult
Solution Approach 1:
The system merges the trip planning of multiple users into a single pooled route. By combining outbound trips to destinations outside the service area with return trips by different users, the system consolidates what would otherwise be separate logistical operations into unified routes, reducing overall complexity.
Solution Approach 2:
The system uses automated algorithms to match users and compute pooled routes without requiring manual intervention. The computational matching process automatically handles the complexity of coordinating multiple users, vehicles, and routes, allowing the system to manage extended service areas through self-service automation rather than manual logistics.
3Adaptability or versatility
If pooled routes are computed to allow trips outside the service area, then the service area coverage is extended, but the computational complexity of route optimization increases
Solution Approach 1:
The system applies threshold-based filtering to reduce the search space before performing detailed route optimization. By first identifying users within threshold proximity and threshold time windows, the system performs partial action (filtering) before the excessive computation of full route optimization, reducing the overall computational burden.
Solution Approach 2:
The system performs preliminary matching of users based on proximity and time thresholds before computing the actual pooled routes. This preliminary action pre-screens potential candidates for pooling, so that the more computationally intensive route optimization is only performed on a reduced set of pre-qualified user pairs, significantly reducing overall computational complexity.
4Productivity
If users are matched based on threshold proximity and threshold time, then the efficiency of vehicle utilization is improved, but the flexibility in route options is reduced
Solution Approach 1:
The system uses adjustable threshold parameters for proximity and time that can be modified based on service conditions, vehicle availability, and user demand. By changing these parameters dynamically, the system balances vehicle utilization efficiency with route flexibility, allowing tighter thresholds during high-demand periods and looser thresholds when expansion is prioritized.
Data Source
AI summary
An approach is provided for generating a pooled route to extend a service area of a shared vehicle. The approach involves receiving a request from a first user to travel a first route to a destination outside of the service area of the shared vehicle. The approach also comprises determining a second user with a second route that uses the shared vehicle and that is within a threshold proximity, a threshold time, or a combination thereof of the first route, the destination, or a combination thereof. The approach further comprises computing the pooled route for the first user to travel to the destination using the shared vehicle and for the second user to return the shared vehicle to the service area after the first user reaches the destination.