Evacuation Route Prediction for Outdoor Disaster Guidance
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Solution Overview
Problem
Existing emergency evacuation systems are inadequate for outdoor disasters such as forest fires, floods, and tornadoes, as they struggle to guide users to safety beyond building premises, and there is a lack of effective methods to induce evacuation in such scenarios.
Innovation Solution
A method and system that utilize prediction data to create safe evacuation routes by predicting the spread of disasters, congestion levels, and travel times in road networks, allowing for the distribution and guidance of users along safe paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If emergency evacuation systems use traditional emergency lighting and speakers to guide evacuation, then evacuation can be prompted within building premises, but the system cannot effectively guide users to safety in outdoor disaster scenarios such as forest fires, floods, and tornadoes
Solution Approach 1:
The evacuation guidance system is transformed from a building-specific emergency lighting and speaker system into a universal navigation system that works across both indoor and outdoor environments. The system uses mobile devices with GPS and navigation applications to provide evacuation guidance, making it applicable to various disaster types including forest fires, floods, and tornadoes, while maintaining reliability through predictive routing algorithms that account for disaster spread patterns
2Loss of information
If users are provided with emergency disaster messages containing information on nearby shelters, then users receive shelter location information, but users cannot be effectively induced to evacuate to those shelters as they must navigate independently
Solution Approach 1:
A predictive routing system acts as an intermediary between shelter location information and users. The system processes shelter information and generates optimized evacuation routes that account for disaster spread predictions, traffic conditions, and real-time safety assessments. This intermediary service transforms raw shelter information into actionable navigation guidance that users can follow through mobile device applications
Solution Approach 2:
The system performs preliminary actions by pre-calculating evacuation routes and predicting disaster spread patterns before users need to evacuate. Traffic conditions, disaster propagation models, and route safety assessments are prepared in advance, allowing users to receive ready-to-follow navigation instructions when emergencies occur, rather than having to make decisions under stress
3Loss of time
If evacuation begins without preliminary guidance predicting disaster spread and traffic congestion, then evacuation can start immediately, but vehicles may encounter traffic jams and dangerous situations that hinder safe evacuation
Solution Approach 1:
The system performs preliminary actions by calculating evacuation routes and predicting disaster spread patterns before evacuation begins. Traffic conditions, congestion hotspots, and safe routing options are pre-assessed, allowing users to start evacuation immediately while following pre-optimized routes that anticipate future traffic problems and disaster progression
Solution Approach 2:
The system implements continuous feedback mechanisms that monitor real-time traffic conditions, disaster spread patterns, and route safety. This feedback is used to dynamically adjust and update evacuation routes during the evacuation process, ensuring users are redirected away from developing congestion or hazard zones while maintaining immediate evacuation capability
Data Source
AI summary
An evacuation inducing method and system are disclosed. The evacuation inducing method includes: detecting the location of an emergency situation in a target region; generating prediction data for each unit path included in the target region, which predicts until when each unit path will remain safe, by predicting a spread of the emergency situation from the location of the emergency situation by using a spread prediction algorithm; predicting the degree of congestion on each unit path included in the target region and the expected travel time by taking into consideration the number of objects included in the target region that is preliminarily identified; creating an evacuation route based on the prediction data, the degree of congestion on each unit path, and the expected travel time; and initiating guidance for distributing and evacuating the objects based on the created evacuation route.