Automated Driving Vehicle Maintenance Worker Assignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In operation management systems for automated driving vehicles, the process of switching from automated driving to manual driving for maintenance and inspection is inefficient due to the time-consuming task of worker assignment, which results in vehicles being on standby, reducing overall operation efficiency.
Innovation Solution
An operation management apparatus that predicts the time point for switching from automated to manual driving, identifies target vehicles with impending maintenance needs, acquires and analyzes vehicle data and operation records to determine abnormalities, and designates a suitable worker from a pool based on job classifications and availability, notifying them to address the issues promptly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If worker assignment is performed manually considering vehicle conditions, worker tasks, and operation states, then the accuracy of worker selection is improved, but the time required for assignment increases
Solution Approach 1:
The system pre-establishes worker profiles with skill classifications and vehicle abnormality type classifications before actual assignment occurs. When a vehicle requires maintenance, the system automatically matches the vehicle's abnormality type with pre-categorized worker skills, eliminating the need for real-time manual assessment and significantly reducing assignment time while maintaining accuracy
Solution Approach 2:
The manual worker assignment process is replaced with an automated information processing system that uses computer algorithms to match vehicle conditions with worker capabilities. The controller automatically retrieves vehicle data, determines abnormality types, queries worker profiles, and designates appropriate workers, substituting human judgment with automated information processing
2Productivity
If worker assignment process is simplified to reduce time, then the operation efficiency is improved, but the quality of worker matching deteriorates
Solution Approach 1:
Worker profiles are pre-established with detailed skill classifications corresponding to different vehicle abnormality types. This preliminary categorization enables the system to perform rapid automated matching without compromising matching quality, as the classification framework is designed in advance to cover all potential vehicle conditions
Solution Approach 2:
The system incorporates feedback mechanisms where worker performance data and vehicle condition data are continuously collected and used to refine the matching algorithm. This feedback loop ensures that the automated assignment process improves over time, maintaining high matching quality while operating efficiently
Data Source
AI summary
An operation management apparatus operates one or more vehicles by automated driving. The operation management apparatus includes a controller configured to predict, for each vehicle based on operation plan data, a time point at which driving is switched from automated driving to manual driving, identify, as a target vehicle, a vehicle for which time until the predicted time point is less than a threshold value, acquire vehicle data and/or operation record data, determine, based on the acquired vehicle data or the acquired operation record data, one or more types of abnormality having occurred in the target vehicle, designate, from among a plurality of workers according to the determined types of abnormality, a first worker who is to perform a maintenance operation on the target vehicle at a site near the target vehicle, and notify the first worker of information that prompts the first worker to take care of the abnormality.