Autonomous Driving Log Storage Control for Memory-Limited Mileage

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Solution Overview

Problem

The limited memory capacity in vehicles using machine learning models for autonomous driving control poses a challenge as log data generated during autonomous driving fills up the memory, potentially leading to a situation where new data cannot be stored, necessitating a solution to prevent this overflow.

Innovation Solution

The system predicts vehicle mileage based on available memory space, adjusting the driving distance to avoid memory overflow by storing log data efficiently and managing memory usage through compression and deletion strategies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If log data is continuously stored in the memory device during autonomous driving control, then the data amount increases and verification capability improves, but the free space of the memory device decreases and may become full

Engineering Contradiction:

Improvedata amount of log dataVSAvoidfree space of memory device

Core Design Contradiction:

Quantity of substanceVSArea of stationary object

Solution Approach 1:

The system performs preliminary action by predicting the mileage before it is actually traveled. The processor calculates expected mileage based on current free space and historical data, and sets the mileage limit in advance. This prevents the memory from becoming full during actual autonomous driving operations, ensuring continuous logging capability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by continuously monitoring the free space of the memory device and adjusting the mileage prediction accordingly. The processor uses the relationship between free space and traveled mileage to refine future predictions, ensuring that the mileage limit is set appropriately to prevent memory overflow while maximizing data collection.

Inventive Principle:

Principle #23Feedback

2Device complexity

If the memory device capacity is limited, then device complexity is reduced, but the ability to store log data continuously is compromised

Engineering Contradiction:

Improvememory device capacityVSAvoidcontinuous data logging capability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies dynamics by making the mileage limit adjustable rather than fixed. The processor dynamically updates the mileage prediction based on the relationship between free space and traveled mileage, allowing the system to adapt to changing memory conditions and maintain reliable continuous logging.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12600378B2Autonomous driving system

Publication Date: 2026.04.14 TOYOTA JIDOSHA KK

AI summary

Processing for autonomous driving control of a vehicle, processing to store log data related to the autonomous driving control in one or more memory devices during an execution of the autonomous driving control, and processing to predict a mileage of the vehicle is executed. In the processing to predict the mileage, a free space of the one or more memory devices in which log data is stored is acquired. In addition, the mileage is set according to the acquired free space. The mileage is set to be shorter as the free space is smaller.