Vehicle Memory Downloading for Crash Data Retention
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Solution Overview
Problem
Current autonomous vehicle technologies lack effective methods to determine the cause of accidents, particularly in cases where software navigation or design failures are suspected, as existing systems fail to fully utilize the hardware and processing power available in autonomous vehicles.
Innovation Solution
A system that rapidly downloads volatile data from autonomous vehicle system memory to non-volatile memory upon detecting an event, such as a collision, and analyzes this data using pattern recognition and machine learning to identify software or design issues, allowing for subsequent configuration or firmware updates to prevent similar incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sensor data is stored in volatile memory during autonomous vehicle operation, then data can be rapidly accessed and processed, but data is lost when power is lost during an accident
Solution Approach 1:
The system performs preliminary action by detecting accident conditions (through sensors monitoring collision, rapid deceleration, or other event parameters) and triggering a data preservation sequence before power is lost. This includes identifying which volatile memory contains critical sensor data and initiating its transfer to non-volatile storage while the system is still operational.
Solution Approach 2:
The patent introduces an intermediary data management system that acts as a bridge between volatile memory and non-volatile storage. This intermediary controller monitors volatile memory for accident conditions and automatically manages the data transfer process, serving as a mediator that protects against power loss without requiring changes to the underlying memory technologies.
2Quantity of substance
If sensor data is compressed to reduce storage space, then storage capacity is increased, but data analysis capability is reduced
Solution Approach 1:
The data management system segments data into different categories (critical accident data, routine operational data, telemetry data) and applies different storage strategies to each segment. Critical sensor data that requires detailed analysis is stored in uncompressed or minimally compressed format, while other data can be compressed, thus preserving analysis capability for the most important information while still achieving storage efficiency.
Solution Approach 2:
Different quality levels of data storage are applied to different types of data based on their analytical requirements. Critical sensor data maintains high fidelity and minimal compression, while less critical data can be stored in more compressed formats. This local differentiation of data quality allows the system to optimize both storage capacity and analysis capability where needed.
Data Source
AI summary
A method includes detecting an event occurring on a vehicle. The vehicle includes at least one computing device that controls at least one operation of the vehicle. The at least one computing device includes a first computing device comprising system memory. In response to detecting the event, data is downloaded from the system memory to a non-volatile memory device of the vehicle. In some cases, a control action for the vehicle is implemented based on analysis of the downloaded data.