Autonomous Vehicle Control for Demand-Based Relocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle control systems for autonomous vehicles lack an efficient method to allocate dropped-off vehicles to appropriate locations, leading to unnecessary re-movement and increased fuel consumption.
Innovation Solution
A vehicle control apparatus that determines a moving destination for a dropped-off vehicle based on its current location, available standby places, and vehicle-demand prediction information, using a processor to instruct the vehicle to move to the determined location, thereby optimizing allocation and reducing re-movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a dropped-off vehicle is allocated to a random or predetermined location, then the vehicle control system is simple to operate, but the vehicle may require unnecessary re-movement leading to increased fuel consumption
Solution Approach 1:
The system performs preliminary actions by predicting future vehicle demand at various standby locations before allocating the dropped-off vehicle. The demand prediction information is obtained in advance, and the moving destination is determined based on this prediction, preventing unnecessary re-movement and reducing fuel consumption while maintaining reasonable system complexity
Solution Approach 2:
The system uses demand prediction information as feedback to dynamically determine the optimal moving destination for dropped-off vehicles. This feedback mechanism allows the system to allocate vehicles to locations where they are most likely to be needed, reducing unnecessary re-movement and fuel consumption without requiring overly complex control logic
2Productivity
If the vehicle is instructed to move to a standby place immediately after drop-off, then the allocation efficiency is improved, but computational overhead and re-issuing of instructions increase
Solution Approach 1:
The system obtains demand prediction information in advance before determining the moving destination. This preliminary action allows the system to make efficient allocation decisions without requiring complex real-time computations, thereby improving allocation efficiency while minimizing computational overhead and instruction re-issuing
Solution Approach 2:
The system determines a moving destination among multiple standby places based on demand prediction, selecting the most appropriate location rather than exhaustively evaluating all possibilities. This partial action approach achieves sufficient allocation efficiency without incurring excessive computational overhead
Data Source
AI summary
When a self-driving vehicle that transfers an object to a predetermined location is left at the predetermined location without the object in the vehicle, a vehicle control apparatus determines a moving destination among a plurality of standby places, based on the current location of the vehicle, the locations of the plurality of standby places, and vehicle-demand prediction information, and instructs the vehicle to move to the determined moving destination.