Vehicle Network Composite Traffic Image Generation
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Solution Overview
Problem
Existing in-vehicle traffic monitoring services provide delayed or schematic representations of traffic conditions, lacking real-time visual monitoring capabilities and efficient processing power to generate composite traffic images, leading to unnecessary resource expenditure.
Innovation Solution
A method and system where vehicles establish external connections to share triggering event signals and capture image data, stitching it into composite real-time traffic images using vehicle-borne sensors and edge computing devices, distributing processing tasks to reduce computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual vehicles generate and process composite real-time traffic images, then real-time visual traffic monitoring capability is improved, but computational burden and processing power requirements worsen
Solution Approach 1:
The system divides the computational task of generating composite traffic images into segments distributed across multiple vehicles. Each vehicle captures local image data and transmits it to other vehicles, which then stitch the images together. This segmentation allows real-time visual monitoring without requiring any single vehicle to handle the full computational burden of processing all traffic data independently.
2Productivity
If vehicles continuously monitor traffic patterns, then real-time traffic information is improved, but resource expenditure worsens
Solution Approach 1:
Instead of continuous monitoring, the system uses event-triggered periodic action where vehicles capture and transmit image data only when specific events occur (such as traffic conditions changing or reaching certain thresholds). This approach maintains real-time traffic information availability while significantly reducing resource expenditure by activating sensors and communication only when necessary rather than continuously.
3Area of stationary object
If multiple vehicles share image data and process composite images, then comprehensive traffic coverage is improved, but network communication requirements worsen
Solution Approach 1:
The system merges image data from multiple vehicles to create a comprehensive composite traffic image that covers a larger area than any single vehicle could observe. By combining the camera feeds and image data from several vehicles along the roadway, the system achieves extensive traffic coverage while managing network communication requirements through efficient data sharing protocols and selective image transmission.
Data Source
AI summary
A method of generating composite image data using a first vehicle including a first camera and first network interface hardware and a second vehicle including a second camera and second network interface hardware includes establishing an external connection between the first vehicle and the second vehicle with the first network interface hardware and the second network interface hardware, generating a triggering event signal in the first vehicle in response to a triggering event, sending the triggering event signal to the second vehicle, capturing first image data using the first camera and capturing second image data using the second camera, and stitching the first image data and the second image data into composite image data.