Remote Fleet Monitoring Using Composite Vehicle Scene Replication
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Solution Overview
Problem
Autonomous vehicle fleets face challenges in diagnosing and resolving errors without human intervention, as existing systems require on-site human interaction, which can be dangerous and reduces productivity.
Innovation Solution
A centralized monitoring system that includes autonomous vehicles equipped with sensors, cameras, and controllers, and a remote monitoring station with augmented reality capabilities, allowing operators to remotely diagnose and manage errors by aggregating sensor data and camera images into a time-sequenced composite image file, enabling real-time monitoring and virtual operation of vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of repair
If humans physically enter the workspace to resolve errors in autonomous vehicles, then error resolution capability is improved, but human safety is worsened and productivity is reduced
Solution Approach 1:
The system creates a virtual copy of the autonomous vehicle's environment by aggregating sensor data and camera images into a time-sequenced composite image file. This virtual replica allows operators to remotely observe and diagnose errors without physically entering the workspace, eliminating safety risks while maintaining error resolution capability
Solution Approach 2:
The centralized monitoring station acts as an intermediary between operators and autonomous vehicles. It aggregates sensor data, processes images, and transmits composite views to operators, enabling remote error diagnosis and resolution without direct human intervention in the workspace
2Ease of repair
If humans are stationed nearby to resolve errors, then error response capability is improved, but productivity is worsened due to reduced autonomous operation
Solution Approach 1:
By creating a virtual replica of the vehicle environment through aggregated sensor data and time-sequenced composite images, operators can remotely monitor and respond to errors without being physically present, allowing autonomous vehicles to operate independently and maintain high productivity
Solution Approach 2:
The system replaces the mechanical presence of human operators near vehicles with an electronic monitoring system that aggregates sensor data and transmits composite images remotely, eliminating the need for physical proximity while maintaining error response capability
3Measurement precision
If multiple sensors and cameras are integrated, then diagnostic capability is improved, but system complexity is worsened
Solution Approach 1:
The system merges data from multiple sensors and cameras into a single time-sequenced composite image file. This consolidation integrates multiple data streams into one unified view, improving diagnostic capability while managing system complexity through data aggregation rather than separate processing channels
Data Source
AI summary
An apparatus and method for monitoring the status and health of a fleet of vehicles operating in a common space. A centralized monitoring operator receives status information and has the capability to independently interact with each vehicle in the fleet.