Artificial Horizon Data Transmission for ADAS
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing protocols for creating an artificial horizon in vehicles, such as ADASIS version 2, struggle with efficiently processing and transmitting a high volume of data, particularly with temporary events, which can lead to system slowdown or saturation.
Innovation Solution
The proposed method enhances the ADASIS protocol by adding a dynamic layer to differentiate between static and dynamic temporary events, allowing for more targeted data transmission using long messages with specific encoding for event types, reducing unnecessary data transmission and overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the ADASIS protocol transmits all temporary event data to clients, then complete environmental information is provided, but system saturation and slowdown occur due to excessive data volume
Solution Approach 1:
The patent applies local quality by differentiating between static and dynamic temporary events, applying different transmission strategies to different types of data. Static events are transmitted less frequently while dynamic events requiring immediate attention are transmitted more urgently, optimizing the balance between information completeness and system performance
Solution Approach 2:
The patent changes the parameter of event classification by introducing a distinction between static and dynamic temporary events. This parameter change enables the system to adjust data transmission priorities and frequencies based on event characteristics, reducing unnecessary data transmission while maintaining critical information flow
2Measurement precision
If the system transmits detailed data about all events, then accurate environmental characterization is achieved, but computational load increases causing system saturation
Solution Approach 1:
The patent applies local quality by transmitting detailed characterization data selectively based on event type. Static events receive standard-level detail while dynamic events receive enhanced detail only when necessary, optimizing the balance between measurement precision and computational energy consumption
Solution Approach 2:
The patent applies partial action by transmitting only the necessary portion of event data based on its classification. Rather than transmitting complete detailed data for all events, the system transmits partial data for static events and full data only for dynamic events, reducing overall computational load while maintaining accuracy where needed
Data Source
AI summary
A method for creating an artificial horizon for a motor vehicle includes receiving input data relating to the motor vehicle and to its surroundings; determining different paths; and generating messages characterizing the artificial horizon, including long messages for characterizing events, each long message having multiple fields including at least a first field relating to a type of attribute characterizing the event and a second field indicating the value of the attribute. The first field can have at least two distinct values associated with a corresponding number of temporary event categories, the categories being separated according to their speeds and/or their positions relative to the motor vehicle.