Remote Vehicle Visualization Control With Object Magnification
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Solution Overview
Problem
Current vehicle control systems lack the ability to seamlessly integrate autonomous and remote operation, limiting their efficiency and safety in navigating environments and preventing collisions.
Innovation Solution
A remote station system that uses sensors like LiDAR and cameras to detect objects and obstacles, allowing for remote control of vehicle actions through a processor and display system, which can magnify specific sections of the vehicle's field of view for enhanced control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If purely autonomous vehicle trajectory generation is used, then the vehicle can operate without human intervention, but the system lacks the benefits of user-controlled operation and cannot provide magnified visualization for remote monitoring
Solution Approach 1:
The system dynamically switches between autonomous and remote control modes based on operational needs. The processor can transition from fully autonomous trajectory generation to remote station control, allowing flexible adaptation between automation levels and enabling magnified visualization when remote monitoring is required.
Solution Approach 2:
The vehicle control system integrates multiple functions into a single unified platform that supports both autonomous operation and remote control capabilities. The processor handles both autonomous trajectory generation and remote monitoring tasks, making the system versatile and adaptable to different operational requirements.
2Device complexity
If standard field of view display is used, then the system maintains simple display architecture, but the remote operator cannot see detailed sections of the environment for precise control decisions
Solution Approach 1:
The system adds a magnification dimension to the standard field of view display. By providing both the original FOV and magnified sections simultaneously, the system enables remote operators to view detailed information about specific objects or areas without losing the broader contextual view, thereby improving visual detection precision.
Solution Approach 2:
The display system segments the field of view into multiple regions, with certain areas magnified for detailed inspection while maintaining the overall scene context. This segmentation allows the remote operator to focus on specific objects of interest while preserving awareness of the complete environment.
3Reliability
If remote control with magnified visualization is implemented, then collision avoidance improves, but the system complexity and computational requirements increase
Solution Approach 1:
The processor acts as an intermediary between the sensor data and the remote operator. It processes sensor data to generate magnified visualizations of specific objects or areas, providing enhanced information to the remote operator without requiring direct manipulation of raw sensor data, thereby managing system complexity while improving collision avoidance.
Solution Approach 2:
The system performs preliminary processing of sensor data to identify and magnify relevant objects or areas before presenting them to the remote operator. This preliminary action of selecting and enhancing critical information reduces the computational burden during real-time operation and improves collision avoidance by highlighting important elements in advance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables safe and efficient vehicle operation by combining autonomous detection with remote human intervention, improving collision avoidance and trajectory control.
Implementation Method 1
A LIDAR sensor is configured to emit light, which strikes material (e.g., objects) within the vicinity of the LiDAR sensor. Once the light contacts the material, the light is deflected. Some of the deflected light bounces back to the LiDAR sensor.
Implementation Method 2
The LiDAR sensor is configured to measure data pertaining to the light bounced back (e.g., the distance traveled by the light, the length of time it took for the light to travel from and to the LiDAR sensors)
Data Source
AI summary
Systems (e.g., remote station systems) and methods for remotely controlling a vehicle are provided. The remote station system may comprise a transmitter configured to receive one or more data points and a processor configured to identify one or more objects within a field of view of the vehicle, using the one or more data points and generate a signal to magnify a section of the field of view of the vehicle containing the one or more objects. The remote station system may comprise a display configured to display the one or more data points generated by the one or more sensors and display the one or more objects in a magnified state. The remote station system may comprise one or more remote actuation controls configured generate one or more driving actions. The one or more driving actions may correlate to one or more actuator commands.