Construction of navigational maps for evacuees in disaster areas based on ant colony systems

Asakura, Koichi; Watanabe, Toshio

doi:10.1504/ijkwi.2013.060274

Cited by 10 publications

(2 citation statements)

References 14 publications

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“…In their approach, ants and pheromone of ACO are implemented as software mobile agents, where the agents corresponding to ants dynamically guide evacuees to the evacuation gates in a floor (Avilés et al, 2014). Asakura et al proposed an approach that calculates evacuation routes based on ACO on a simulator, and showed the effectiveness of applying their approach to wide-scale disaster areas (Asakura et al, 2013a) (Asakura et al, 2013b).…”

Section: Related Workmentioning

confidence: 99%

A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization

Goto

Ohta

Matsuzawa

et al. 2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

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This paper reports the results of applying our approach discovering safe evacuation routes to practical situations. Our approach is based on the ant colony optimization (ACO) and it is practical in the light of a real case with a tsunami. ACO have been often employed for finding evacuation routes in traditional approaches, which only take advantage of ants' behavior more frequently following traces of other ants through pheromone communications. We assume that there are a lot of danger zones in the damaged area. For example Rikuzentakata is a city that extensively damaged in the 2011 Great East Japan Earthquake. In such a case, the traditional approaches may present some unsafe routes through the danger zones. We have proposed an ACO based approach that calculates evacuation routes avoiding danger zones. In our approach, evacuees can deposit deodorant pheromone around danger zones, which makes normal pheromone ineffective, so that our approach gives routes not passing through the danger zones. We have implemented our approach as a simulator, conducting experiments in the same situation as the Rikuzentakata case. Through the results of the experiments, we show that our approach decreases the number of people suffering from collapsed and burning buildings.

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Section: Related Workmentioning

confidence: 99%

A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization

Goto

Ohta

Matsuzawa

et al. 2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

View full text Add to dashboard Cite

show abstract

“…In their system, some evacuees record road information while moving to shelters, and then exchange the information they have collected using a MANET. Since the situation can change from time to time in a disaster area, they have proposed an ACO-based extension to allow evacuees to respond to such changes (Asakura et al, 2013). In our proposed system, we have also introduced MANETs and multi-agent system.…”

Section: Introductionmentioning

confidence: 99%

Multi-agent Approach for Return Route Support System Simulation

Taga

Matsuzawa

Takimoto

et al. 2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

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We propose a system that supports stranded commuters caused by a large-scale disaster. When a large-scale disaster breaks out, buildings may collapse and roads may be damaged and the public transportation systems would be paralyzed. Thus, people working in the city center have to walk back home on foot. The problem is that when those people start walking, the situation along the routes for returning home may be different from that of the pre-disaster. Not only may it be the first time for most of them to walk home, but also the return route may be extremely complex due to many detours. They have to look for alternative routes whenever bridges collapse and fires break out. Making situation become worse, modern people intensively use navigation systems, those systems may be unavailable due to the paralyzed Internet. A large scale disaster may destroy base stations of wireless phones, and even if it does not completely destroy them, extreme congestion may paralyze the communication infrastructure so that not only net-surfing using smartphone, but also collecting information by e-mail may become impossible. To deal with such situations, we are designing a system that provides those unfortunate pedestrians appropriate return routes to their homes without depending on the communication infrastructures. Instead, our proposed system only depends on smartphones of those pedestrians and constructs mobile ad hoc networks (MANET) to collect and disperse useful information. We employ multiple mobile agents extensively for information collection and dispersion. In order to demonstrate the feasibility of our system, we have constructed a preliminary prototype of the simulation system and have conducted numerical experiments.

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A Movement Algorithm for Evacuee Agents in Disaster Simulators: Towards the Development of Evacuation Guidance Systems Based on Ant Colony Systems Using MANET

Asakura

Watanabe

2015

Intelligent Interactive Multimedia Systems and Services

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Construction of navigational maps for evacuees in disaster areas based on ant colony systems

Cited by 10 publications

References 14 publications

A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization

A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization

Multi-agent Approach for Return Route Support System Simulation

A Movement Algorithm for Evacuee Agents in Disaster Simulators: Towards the Development of Evacuation Guidance Systems Based on Ant Colony Systems Using MANET

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