Autonomous Vehicle Fleet Monitoring for Remote Error Diagnosis
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Solution Overview
Problem
Autonomous vehicle fleets face challenges in diagnosing and resolving errors without human intervention, as many systems are not equipped with user controls, and human interaction can be dangerous and reduce productivity.
Innovation Solution
A centralized monitoring system that includes autonomous vehicles equipped with sensors, cameras, and controllers, and a remote monitoring station with a computer, user input device, and display device, allowing for real-time data aggregation and transmission of time-sequenced composite image files to enable remote diagnosis and control of autonomous vehicles using augmented reality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of repair
If human operators physically enter the workspace to resolve errors in autonomous vehicles, then the errors can be directly diagnosed and fixed, but human safety is compromised and productivity is reduced
Solution Approach 1:
The system creates a virtual copy of the autonomous vehicle's environment by capturing images from the vehicle's cameras and sensors, and rendering them in a virtual workspace. This virtual copy allows operators to diagnose and resolve errors remotely without physically entering the hazardous workspace, thus maintaining error resolution capability while eliminating safety risks.
Solution Approach 2:
The system introduces a virtual workspace as an intermediary between the operator and the physical autonomous vehicle. This intermediary environment allows the operator to interact with the vehicle's sensors and cameras remotely, enabling error diagnosis and resolution without direct physical presence in the workspace.
2Ease of repair
If human operators are stationed on standby to handle errors, then error resolution is enabled, but productivity gains from autonomous operation are reduced
Solution Approach 1:
By creating a virtual copy of the workspace and vehicle state, the system enables remote diagnostics without requiring physical presence. Operators can respond to errors as they occur from remote locations, maintaining autonomous operation during normal conditions and only intervening when necessary, thus preserving productivity gains.
Solution Approach 2:
The system continuously captures and stores sensor data and images from autonomous vehicles, preparing the virtual workspace in advance. When an error occurs, the operator can immediately access the pre-prepared virtual environment for rapid diagnosis, reducing downtime and maintaining high productivity.
3Extent of automation
If autonomous vehicles lack user controls for manual operation, then autonomous operation is maintained, but the ability to manually intervene when errors occur is lost
Solution Approach 1:
The system creates a virtual replica of the autonomous vehicle's sensor inputs and camera views, allowing operators to interact with the vehicle environment remotely. This virtual copy provides manual control capability without requiring physical presence or modification of the vehicle's autonomous systems.
Solution Approach 2:
The system replaces physical mechanical controls with a virtual interface. Instead of requiring the operator to physically enter the vehicle or be present in the workspace, the operator interacts with a virtual representation of the vehicle's sensors and environment through a computer interface, enabling manual intervention while maintaining autonomous operation.
Data Source
AI summary
An apparatus and method for monitoring the status and health of a fleet of autonomous vehicles operating in a common space. A centralized monitoring operator receives status information and has the capability to independently interact with each autonomous vehicle in the fleet.