Vehicle Camera Data Prioritization for Distributed ADAS Processing
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Solution Overview
Problem
Current vehicle imaging systems face challenges in efficiently processing the growing amount of data for driver assistance systems, leading to bandwidth and processor speed demands that result in bottlenecks, which can be mitigated by redistributing computation workloads across underutilized integrated circuits and leveraging cloud and fog processing for real-time data analysis.
Innovation Solution
The system utilizes CMOS cameras to capture image data and processes higher priority tasks locally while shifting lower priority tasks to other processors within the vehicle or to remote processors, including cloud-based systems, using artificial intelligence for data analysis and load distribution across vehicle and infrastructure networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If all image data processing is performed locally in the vehicle, then real-time processing speed is improved, but processor bandwidth and computational load increase causing bottlenecks
Solution Approach 1:
The patent segments image data processing into multiple priority levels (first priority, second priority, third priority). First priority tasks (e.g., safety-critical object detection) are processed locally in real-time, while second and third priority tasks are offloaded to remote servers. This segmentation resolves the contradiction by maintaining fast local processing for critical functions while reducing overall processor bandwidth demand through selective offloading.
Solution Approach 2:
The patent introduces a communication system as an intermediary between the vehicle's local processor and remote servers. This intermediary enables selective data transmission based on priority levels, allowing the system to offload non-critical processing tasks while maintaining real-time responsiveness for critical tasks, thereby reducing processor bandwidth demands without sacrificing essential processing speed.
2Loss of time
If more processing tasks are handled locally, then real-time decision-making is improved, but energy consumption and thermal load increase
Solution Approach 1:
The patent segments processing tasks by priority and offloads lower-priority tasks to remote servers, reducing local processor energy consumption and thermal load while maintaining real-time decision-making capability for high-priority safety-critical tasks through local processing.
Solution Approach 2:
The patent applies partial processing locally (only essential high-priority tasks) and partial processing remotely (lower-priority tasks), optimizing the balance between real-time decision-making and energy consumption by performing only the necessary portion of processing locally.
3Productivity
If data is transmitted to remote servers for processing, then computational load is reduced, but data transmission bandwidth and latency increase
Solution Approach 1:
The patent segments data transmission by priority levels, transmitting only essential high-priority data locally for immediate processing while sending lower-priority data to remote servers. This segmentation reduces data transmission bandwidth requirements and latency for critical tasks while still utilizing remote processing capacity for non-urgent tasks.
Solution Approach 2:
The patent implements local quality processing by handling different types of data with different quality requirements locally versus remotely. High-priority safety-critical data receives full local processing attention with minimal transmission delay, while lower-priority data can tolerate remote processing with higher latency, optimizing overall system productivity.
Data Source
AI summary
A vehicular driving assistance system includes an exterior viewing camera disposed at a vehicle and viewing exterior of the vehicle. Image data captured by the camera is provided to and processed at an electronic control unit (ECU). The ECU performs processing tasks for multiple vehicle systems. The vehicular driving assistance system is operable to wirelessly upload captured image data to the cloud for processing at a remote processor. Processing tasks with a higher priority are determined at the ECU to be higher priority tasks. Responsive to determination at the ECU of a higher priority task, the vehicular driving assistance system (i) processes captured image data at the ECU for the higher priority task and (ii) uploads captured image data to the cloud for processing at the remote processor of processing at the remote processor.