CAN to ROS Data Conversion for Autonomous Vehicle Processing
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Solution Overview
Problem
Autonomous vehicles face delays in processing large quantities of sensor data, which can lead to delayed reactions to critical events, such as pedestrians entering their path, due to the time-consuming conversion of raw sensor data into usable Robotic Operating System (ROS) data.
Innovation Solution
The system facilitates communication between an internal computing system and vehicle electronic control units by processing Control Area Network (CAN) data using a Robotic Operating System (ROS) protocol, with an advanced driving interface module driver converting CAN data into ROS data for timely decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If raw sensor data is converted to ROS data using traditional methods, then data processing completeness is improved, but processing time increases causing delays in critical event response
Solution Approach 1:
The patent segments the data processing pipeline into two distinct pathways: a rapid CAN data processing pathway for time-critical events, and a complete ROS data conversion pathway for comprehensive analysis. This segmentation allows the system to process data at different levels of detail depending on the urgency of the situation, thereby reducing overall processing time while maintaining data completeness when needed.
Solution Approach 2:
The system performs preliminary processing of CAN data to identify critical events before full ROS conversion is required. By detecting urgent situations early through streamlined CAN data analysis, the system can trigger appropriate responses without waiting for the slower but more complete ROS data processing to finish, thus reducing response delays.
2Ease of operation
If all sensor data is processed through ROS protocol, then data usability is improved, but processing speed decreases
Solution Approach 1:
The patent applies local quality by processing data at different quality levels based on the specific application need. Critical safety-related data receives full ROS protocol processing for maximum usability, while less time-sensitive data is processed through the faster CAN protocol pathway. This localized quality approach ensures data usability is optimized for each specific use case without uniformly sacrificing processing speed across all data streams.
Solution Approach 2:
The system dynamically changes processing parameters based on the type and urgency of data being processed. For time-critical events, the processing depth and protocol conversion parameters are adjusted to favor speed. For non-critical data, parameters are set to maximize completeness and usability. This parameter adaptation allows the system to balance speed and usability based on real-time requirements.
Data Source
AI summary
Methods and systems are provided for facilitating communications between an internal computing system and vehicle electronic control units. In some aspects, methods and systems are provided and can include receiving data from a plurality of vehicle electronic control units, the data from the plurality of vehicle electronic control units being processed by utilizing a control area network protocol, processing the data received from the plurality of vehicle electronic control units by utilizing a robotic operating system protocol, and providing robotic operating system data based on the data processed by utilizing the robotic operating system protocol to an internal computing system.