AR Traffic Infrastructure Visualization via Edge Server Segmentation
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Solution Overview
Problem
Drivers face challenges in navigating safely due to reduced visibility of traffic infrastructures caused by adverse weather conditions, road degradation, or faded signs, which can lead to accidents.
Innovation Solution
An augmented reality system that uses an edge server, map server, and historical traffic data server to generate and display virtual images of traffic infrastructures within a vehicle's field of view, ensuring visibility regardless of environmental or infrastructure conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers rely on traditional visual observation of traffic infrastructures, then the system remains simple and requires no additional technology, but visibility is reduced under adverse weather conditions, road degradation, or faded signs
Solution Approach 1:
The patent introduces an intermediary system consisting of infrastructure sensors, edge servers, and augmented reality displays that mediate between the physical traffic infrastructure and the driver's perception. Sensors detect traffic infrastructure elements, edge servers process and generate augmented reality images, and displays present enhanced visual information to drivers, ensuring reliable visibility under all conditions without requiring complex driver actions
Solution Approach 2:
The system creates virtual copies of traffic infrastructure elements (lane markings, signs, lights) as augmented reality images that are overlaid on the driver's field of view. These digital copies ensure that even when physical infrastructure is faded, damaged, or obscured by weather, accurate visual representations are maintained and presented to drivers
2Reliability
If the system processes real-time sensor data and generates augmented reality images for every vehicle, then visibility is enhanced, but computational load and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-processing sensor data, pre-generating augmented reality images, and pre-positioning computational resources at edge servers closer to vehicles. This allows the system to have processing results ready before vehicles arrive, reducing actual delivery time and ensuring immediate availability of enhanced visual information when vehicles enter the service area
Solution Approach 2:
The patent extracts processing functions from centralized remote servers and places them at distributed edge servers located closer to vehicles. This extraction reduces data transmission distances, minimizes network latency, and enables faster generation and delivery of augmented reality images, thereby reducing overall processing time while maintaining enhanced visibility
3Adaptability or versatility
If the system covers a large geographic area with multiple edge servers, then more vehicles benefit from enhanced visibility, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent segments the large geographic coverage area into multiple smaller zones, each served by a dedicated edge server. This segmentation allows the system to manage complexity locally at each server while collectively providing broad geographic coverage. Each edge server handles a specific area independently, reducing the computational burden on individual servers while expanding overall system capability
Solution Approach 2:
The edge servers are designed with multi-functionality to handle various tasks including sensor data reception, augmented reality image generation, vehicle communication, and coordination with adjacent servers. This universal design reduces the need for specialized infrastructure at each location, simplifying deployment while enabling extensive geographic coverage through standardized, versatile server units
Data Source
AI summary
A method includes receiving a service request from a vehicle within a geographic area, receiving a first set of data from the vehicle comprising a position of the vehicle within the geographic area, a direction that the vehicle is facing, and a field of view for an augmented reality display associated with the vehicle, obtaining historical traffic data associated with the geographic area, identifying one or more traffic infrastructures within the field of view of the augmented reality display based on a map associated with the geographic area, the historical traffic data, the position of the vehicle, and the direction the vehicle is facing, generating an augmented reality image for the one or more traffic infrastructures based on the historical traffic data and the field of view of the augmented reality display, and sending the augmented reality image to the vehicle.