Dynamic Delay Management for Networked Vehicle Resource Allocation
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Solution Overview
Problem
Existing manual systems for managing networked vehicle resources, such as private hire vehicles, struggle to efficiently handle real-time road conditions and driver availability during busy periods, leading to suboptimal response times and increased 'Fully Booked' settings.
Innovation Solution
An automated system that dynamically introduces additional delays in busy regions by analyzing the ratio of unallocated bookings to available vehicles and applying rules to adjust delay times based on work volume, allowing for real-time optimization of vehicle and driver allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual allocation by controller is used, then flexibility in handling real-time conditions is improved, but response time and productivity deteriorate
Solution Approach 1:
The system enables automatic allocation where the allocation system itself performs the assignment of vehicles to bookings without human intervention. The system monitors driver locations, analyzes road conditions, and automatically assigns bookings to appropriate drivers based on real-time data, eliminating the need for manual controller intervention while maintaining adaptability to changing conditions.
Solution Approach 2:
The system continuously monitors real-time road conditions, driver locations, and booking status, using this feedback to dynamically adjust allocations. The system processes ongoing data from multiple sources and automatically recalculates optimal assignments, ensuring flexibility in handling real-time conditions while maintaining high productivity through automated decision-making.
2Productivity
If automated allocation is implemented, then response time is improved, but adaptability to real-time road conditions deteriorates
Solution Approach 1:
The automated system incorporates continuous feedback loops that monitor real-time road conditions, driver status, and booking requirements. This feedback enables the system to dynamically adjust allocations based on current conditions, maintaining adaptability while achieving fast automated response times.
Solution Approach 2:
The allocation system is designed to be dynamic, continuously updating allocations based on changing real-time conditions. The system can rapidly reassign bookings when road conditions change or drivers become unavailable, maintaining adaptability through automated real-time decision-making rather than static pre-planned allocations.
3Device complexity
If default delay times are used, then system simplicity is maintained, but service efficiency during busy periods deteriorates
Solution Approach 1:
The system dynamically adjusts delay times based on real-time conditions such as driver availability, road conditions, and booking urgency. During busy periods, the system automatically reduces delays for critical bookings while maintaining appropriate delays for non-urgent ones, optimizing service efficiency without requiring complex manual intervention.
Solution Approach 2:
The system automatically changes the delay time parameter based on real-time conditions and booking priorities. Rather than using fixed default delays, the system adjusts this parameter dynamically according to factors such as driver location, road conditions, and customer requirements, improving service efficiency while maintaining automated operation.
4Reliability
If additional delays are introduced in busy regions, then driver availability is improved, but customer response time deteriorates
Solution Approach 1:
The system applies different delay adjustments to different regions and different bookings based on local conditions. In busy regions where driver availability is critical, the system may introduce selective delays for non-urgent bookings while maintaining fast response times for urgent bookings or in regions with driver shortages. This localized approach ensures driver availability is improved without unnecessarily delaying all customers.
Solution Approach 2:
The system dynamically changes delay parameters based on real-time analysis of driver availability, regional demand, and booking priorities. Rather than applying uniform delays, the system adjusts this parameter selectively to optimize both driver availability and customer response time based on current conditions.
Data Source
AI summary
A method and apparatus for managing a networked vehicle resource sharing facility, the method and system provide for:defining a geographical area as a work region;storing, in a data structure, data relating to vehicle hire bookings beginning inside the work region, wherein the booking information for each booking includes a default delay time;applying a rule to determine that an additional delay condition or fully booked condition is satisfied within the work region; andin response to positively determining, automatically introducing an additional delay or a fully booked setting, respectively, to at least some of the vehicle hire bookings inside the work region.