Fleet Task Bidding Platform for Cross-Fleet Resource Sharing
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Solution Overview
Problem
Fleet operators face challenges in optimizing resource utilization due to fluctuations in demand, leading to underutilization or overutilization of vehicles and drivers, which can be addressed through a bidding mechanism that balances resources between fleets.
Innovation Solution
A system and method for resource sharing among vehicle fleets using a bidding mechanism, where real-time data is used for machine learning-based price estimation and scheduling optimization, incorporating vehicle, driver, and task data to allocate tasks and resources efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fleet operators independently manage their vehicle resources, then each fleet maintains operational control and scheduling flexibility, but resource utilization becomes inefficient with underutilized vehicles in some fleets and overutilized vehicles in others
Solution Approach 1:
The patent merges multiple independent fleet management systems into a unified platform where vehicles from different fleets can be shared and allocated dynamically. The online platform combines scheduling algorithms, bidding mechanisms, and real-time monitoring to coordinate resources across fleet boundaries, transforming individual fleet operations into a collaborative ecosystem that optimizes overall resource utilization.
Solution Approach 2:
The online platform serves multiple functions simultaneously: it acts as a marketplace for task bidding, a scheduling system for route optimization, a monitoring system for real-time tracking, and a settlement system for payment processing. This multi-functional design enables the system to handle diverse fleet operations through a single unified interface, reducing the need for separate management systems.
2Productivity
If fleet operators share resources through a bidding mechanism, then resource allocation efficiency improves and underutilized vehicles are optimized, but the complexity of coordination and communication between fleets increases
Solution Approach 1:
The bidding mechanism enables fleets to autonomously negotiate and allocate tasks without requiring direct manual coordination. Each fleet independently submits bids based on their vehicle availability and task requirements, and the automated matching system handles the allocation process. This self-service approach reduces coordination overhead while maintaining efficient resource sharing.
Solution Approach 2:
The system implements real-time feedback loops where bidding results, task completion status, and vehicle availability information are continuously updated and communicated to all participating fleets. This feedback mechanism enables dynamic adjustment of bidding strategies and resource allocation decisions, simplifying coordination through transparent, data-driven communication.
3Measurement precision
If real-time data is collected and processed for bidding proposals, then price estimation accuracy improves and optimal scheduling is achieved, but data processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary data processing by pre-calculating baseline price estimates, vehicle suitability scores, and route optimization parameters before bidding occurs. Historical data is pre-processed to establish pricing models and performance metrics, enabling rapid real-time decision-making during actual bidding without requiring extensive computational analysis at the moment of task allocation.
Data Source
AI summary
A system and method for resource sharing among vehicle fleets using a bidding mechanism is presented. A fleet scheduler generates a bidding proposal for one or more unassigned tasks associated with a first fleet of vehicles, where the bidding proposal is associated with a second fleet of vehicles associated with an excess quantity of resources. An online platform receives the bidding proposal for the one or more unassigned tasks and determines, using the bidding proposal and based on an auctioning scheme, one or more winning bids. The one or more winning bids includes assigning the one or more unassigned tasks from the first fleet of vehicles to the second fleet of vehicles with the excess quantity of resources.