Response Vehicle Deployment via Virtual Damage Models
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Solution Overview
Problem
Traditional methods for deploying response vehicles in areas impacted by damage-causing events are unreliable due to untraversable roadways and the inability to accurately assess post-disaster conditions, as they rely on pre-event mapping data.
Innovation Solution
A computer-implemented method and system that generates a virtual model of the affected region using images captured by remote imaging vehicles, allowing for the deployment of response vehicles to specific target locations based on current damage conditions, with route generation accounting for damaged areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping techniques are used for response vehicle deployment, then pre-event road network data is available, but the routes become unreliable after damage-causing events block or make roadways untraversable
Solution Approach 1:
The system performs preliminary actions by capturing images of the region before the damage-causing event and generating a virtual model in advance. This pre-generated virtual model serves as the baseline for subsequent route planning after the event, allowing the system to adapt to changed conditions while having pre-prepared reference data.
Solution Approach 2:
The system creates a virtual copy (virtual model) of the physical region based on pre-event images. This virtual model is then used to simulate and plan routes that account for post-event damage conditions, allowing reliable route generation without requiring real-time physical surveying of damaged areas.
2Measurement precision
If virtual models are generated using remote imaging vehicles after damage-causing events, then accurate post-event mapping is achieved, but the complexity of data collection and processing increases
Solution Approach 1:
The system uses an intermediary approach by employing remote imaging vehicles (drones, satellites, or other unmanned platforms) to capture images of the damaged region. These vehicles serve as mediators between the ground truth and the virtual model generation process, allowing accurate mapping without requiring complex ground-based surveying operations.
Solution Approach 2:
The system replaces complex mechanical surveying and manual mapping operations with automated image capture and processing systems. By using remote imaging vehicles and automated algorithms to generate virtual models from images, the system reduces the complexity of data collection and processing while maintaining high mapping precision.
3Productivity
If response vehicles are deployed to target locations in damaged areas, then response effectiveness is improved, but the risks to personnel increase due to untraversable roadways and unsafe conditions
Solution Approach 1:
The system incorporates feedback mechanisms by continuously updating the virtual model with post-event images and using this updated information to generate safe routes. The feedback loop ensures that route plans are based on current conditions, allowing response vehicles to reach target locations effectively while avoiding dangerous areas identified through recent imaging.
Solution Approach 2:
The system creates a virtual copy of the damaged region that accurately represents current conditions, including blocked roadways and unsafe areas. By planning routes within this accurate virtual model, the system can guide response vehicles to target locations while avoiding harmful factors, thereby improving response effectiveness without compromising personnel safety.
Data Source
AI summary
Computer implemented methods and systems for deploying response vehicles based on a virtual environment. A server may obtain a virtual model of an overall region wherein the virtual model was generated based upon a plurality of images captured by a remote imaging vehicle. The server may then provide the virtual model to a user electronic device for rendering in a virtual environment. The server may then determine a target location within the overall region at which the response vehicle should be deployed and generate a route for the response vehicle to follow. The route may be based on damage indicated by the virtual model of the overall region. The server may then provide the route to the user electronic device and/or the response vehicle.