Robotic Delivery Dispatch Using Opportunity Cost Comparison
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Solution Overview
Problem
Unmanned Aerial Vehicles (UAVs) and Autonomous Ground Vehicles (AGVs) are underutilized for delivery due to perceived expense, and users lack transparent comparison of delivery costs across traditional and robotic services.
Innovation Solution
A system that allows users to select delivery options through a mobile application, which communicates with a server to present multiple delivery options, including UAV/AGV services, by considering opportunity costs and past user behavior, and dispatches the appropriate robotic delivery mechanism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional delivery services are used, then delivery cost is lower, but delivery speed and convenience are reduced
Solution Approach 1:
The system changes the parameter of cost transparency by implementing dynamic pricing that displays total costs (product + delivery) to consumers. This allows users to see the true cost comparison between traditional and robotic delivery options, enabling informed decisions that can increase utilization of autonomous vehicles during off-peak periods.
Solution Approach 2:
The system implements dynamic pricing and dispatch mechanisms where delivery options, pricing, and availability are adjusted in real-time based on demand, time of day, and vehicle availability. This dynamic approach allows traditional and robotic delivery services to compete more effectively across different time periods.
2Productivity
If robotic delivery services are deployed, then delivery efficiency increases, but perceived expense increases
Solution Approach 1:
The system implements feedback loops where consumer delivery preferences and cost sensitivities are continuously monitored. This feedback informs dynamic pricing adjustments and service optimization, allowing the system to reduce perceived costs by matching delivery options to consumer willingness to pay while maintaining high utilization of robotic vehicles.
Solution Approach 2:
The system changes pricing parameters dynamically based on utilization rates, time of day, and demand patterns. By adjusting prices to reflect actual operational costs and demand elasticity, the system makes robotic delivery more attractive to consumers while ensuring economic viability.
3Ease of operation
If multiple delivery options are presented to users, then user choice and satisfaction improve, but system complexity increases
Solution Approach 1:
The system implements a universal platform that handles multiple delivery modes (traditional and robotic) through a single interface. This multi-functional system consolidates what would otherwise require separate ordering systems, reducing overall complexity while maintaining diverse delivery options for users.
Solution Approach 2:
The system introduces an intermediary dispatch module that acts as a mediator between consumers and delivery providers. This intermediary automatically processes orders, matches consumers with appropriate delivery options, and coordinates logistics, simplifying the user experience while managing the complexity of coordinating multiple delivery services.
Data Source
AI summary
A distributed robotic delivery system includes a mobile application, a server, a dispatch module, and a plurality of robotic delivery vehicles. The mobile application receives an item cost, robotic delivery shipping options, and acquisition factors. The mobile device displays the item cost, robotic delivery shipping options, and the acquisition factors in a user interface. Upon a selection of robotic delivery option, the mobile application notifies the dispatch module to deploy the robotic delivery vehicle with the item to the specified delivery point.