Autonomous Fleet Repositioning for Predicted Rental Demand
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Solution Overview
Problem
Conventional vehicle rental businesses often have vehicles located far from potential renters, making them inaccessible and leading to inefficient rental processes, as vehicles are typically moved away from rental locations after initial use, resulting in mismatched demand and availability.
Innovation Solution
A system and method for repositioning autonomous vehicles by establishing network connections with vehicles, determining demand through user location data, and relocating vehicles to optimize their placement based on demand, ensuring they are more accessible to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vehicles are initially positioned at a location close to where the prospective renter is located, then accessibility and rental likelihood are improved, but the vehicle will be moved away from this location after rental, causing future mismatch with demand
Solution Approach 1:
The system performs preliminary actions by proactively relocating vehicles to anticipated demand locations before rental requests are made. The server analyzes historical data, current location, and demand patterns to determine optimal relocation targets, then instructs vehicles to move autonomously to these locations in advance, ensuring availability when needed.
Solution Approach 2:
The system implements continuous feedback loops by monitoring vehicle locations, rental requests, and demand patterns in real-time. The server receives updates on vehicle status and location, compares actual performance against targets, and dynamically adjusts relocation instructions to optimize vehicle distribution across the fleet based on evolving demand conditions.
2Device complexity
If conventional vehicle rental businesses are located at centralized locations, then operational control is simplified, but vehicles become far from potential renters, reducing accessibility and rental efficiency
Solution Approach 1:
The system replaces manual fleet management mechanics with automated electronic control. The server computer automatically analyzes location data, determines optimal destinations, and transmits relocation instructions to vehicles via network communications, eliminating the need for manual intervention while maintaining simplified centralized management.
Solution Approach 2:
Vehicles autonomously execute relocation by navigating to server-instructed destinations without human intervention. The autonomous vehicle receives relocation instructions, independently determines the optimal route, and autonomously navigates to the target location, performing the relocation service itself rather than requiring external assistance.
3Ease of operation
If vehicles are relocated frequently to match demand, then accessibility is improved, but energy consumption and operational complexity increase
Solution Approach 1:
The system applies partial action by selectively relocating only those vehicles and to those destinations where demand exists, rather than moving all vehicles continuously. The server evaluates each vehicle's location, demand conditions, and operational status to determine whether relocation is necessary, avoiding unnecessary energy consumption while maintaining accessibility where needed.
Data Source
AI summary
Systems and methods for repositioning autonomous vehicles are disclosed. The systems and methods facilitate moving vehicles of a fleet of vehicles into more advantageous locations. For example, autonomous vehicles can be moved from positions where a vehicle would be difficult to access by a user and/or be less likely to be used by a user to positions that provide easier access by a user and/or make the vehicle more likely to be used.