Vehicle Task Prioritization via Operator Cost Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems lack an efficient method to prioritize the order in which human operators should attend to the needs of multiple autonomous vehicles requiring assistance, especially when multiple vehicles require assistance simultaneously.
Innovation Solution
A system that determines a preferred order for operators to attend to tasks based on urgency metrics and task durations associated with each vehicle, using a method that calculates an order cost for each possible order and selects the order with the lowest cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If operators attend to vehicles in arbitrary order, then all vehicles eventually receive assistance, but the total time to assist all vehicles increases and urgency is not optimized
Solution Approach 1:
The system changes the parameter of task sequencing by calculating an order cost for each possible permutation of tasks based on urgency metrics and task durations. This transforms the arbitrary ordering into an optimized sequence that minimizes total assistance time while prioritizing urgent vehicles.
Solution Approach 2:
The system performs preliminary calculation of the optimal task order before operators begin assistance. By pre-computing the sequence that minimizes total time based on urgency metrics and estimated task durations, the system ensures that operators immediately begin with the most efficient assignment without wasting time on suboptimal sequencing.
2Reliability
If operators prioritize high urgency vehicles, then urgent needs are met faster, but operators may spend excessive time on single vehicles rather than distributing assistance
Solution Approach 1:
The system changes the parameter of task selection by incorporating both urgency metrics and task duration estimates into an order cost calculation. This transforms simple urgency-based prioritization into a balanced optimization that considers both the criticality of the vehicle's need and the time required to complete the task, ensuring operators distribute time efficiently across multiple vehicles.
Data Source
AI summary
A method is provided. The method comprises, for respective vehicles of a plurality of vehicles: (i) determining an urgency metric associated with the vehicle, the urgency metric being indicative of urgency in which to perform a task associated with the vehicle, and (ii) determining a length of time associated with performing the task for the vehicle, the task being performed by an operator of one or more operators, the one or more operators being located remote from the plurality of vehicles and being responsible for monitoring and/or controlling the plurality of vehicles. The method further comprises determining a preferred order in which the one or more operators are to perform the tasks based on the lengths of time and the urgency metrics associated with the plurality of vehicles.