Vehicle Software Update Prediction System
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Solution Overview
Problem
Vehicles with varying characteristics and operating conditions may not achieve significant improvements from software updates, leading to unnecessary updates when expected effects are not realized.
Innovation Solution
An information processing system that acquires vehicle data, predicts the effect of software updates based on this data, and delivers updates only when the predicted effect meets a predetermined reference, withholding updates if the effect is not satisfactory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software update is performed on all vehicles regardless of characteristics and operating conditions, then software update coverage is improved, but resource waste increases due to unnecessary updates
Solution Approach 1:
The patent applies preliminary action by predicting the effect of software update before actually performing the update. The prediction unit estimates the improvement effect based on vehicle data, and only vehicles with predicted effects meeting a reference criterion receive updates. This prevents unnecessary updates and resource waste while ensuring effective updates are delivered.
2Speed
If software update is performed without predicting effect, then update delivery speed is improved, but update appropriateness deteriorates due to unnecessary updates
Solution Approach 1:
The patent performs the prediction of update effect as a preliminary action before delivery. The prediction unit calculates the expected improvement effect based on vehicle characteristics and operating conditions, allowing the delivery unit to make informed decisions about which vehicles should receive updates, thus ensuring appropriateness without significantly delaying the update process.
Solution Approach 2:
The system uses vehicle data that is already being collected for other purposes (such as performance monitoring and diagnostics) to perform the prediction. This self-service approach leverages existing data infrastructure, minimizing the additional time and resources required for prediction while maintaining high update appropriateness.
3Measurement precision
If vehicle-specific prediction is performed for each vehicle, then update appropriateness is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal prediction model that can be applied to all vehicles in the fleet. The prediction unit uses a standardized approach that processes vehicle data according to common criteria, allowing the same system to serve multiple vehicles with different characteristics. This reduces complexity compared to having separate prediction systems for each vehicle type while still maintaining vehicle-specific prediction accuracy.
Data Source
AI summary
A software update system includes: a vehicle data acquiring unit configured to acquire data on a state of a vehicle including data of a predetermined performance of the vehicle; an effect predicting unit configured to predict an effect on the predetermined performance which is obtained when update data of software used in the vehicle for improvement of the predetermined performance is applied to the vehicle based on the data acquired by the vehicle data acquiring unit; and a delivery unit configured to deliver the update data to the vehicle when the effect predicted by the effect predicting unit satisfies a predetermined reference and to withhold delivery of the update data to the vehicle when the effect predicted by the effect predicting unit does not satisfy the predetermined reference.