Development of a mutual assistance evacuation model considering the diversity of residents’ behavior and vehicle ownership : A case study in Mount Merapi, Indonesia

住民行動の多様性と車両保有状況を考慮した共助型避難モデルの開発 : インドネシア・メラピ山におけるケーススタディ

Development of a mutual assistance evacuation model considering the diversity of residents’ behavior and vehicle ownership : A case study in Mount Merapi, Indonesia

Degree Grantors Yamaguchi University

Indonesia has extreme risk of natural disasters because of its position at the confluence of four tectonic plates: the Asian Continent, the Australian Continent, the Indian Ocean, and the Pacific Ocean. The volcano eruption is one of the geological disasters that frequently occur in this country. Mount Merapi is Indonesia’s most active volcano and is famous worldwide. The evacuation crisis in 2010, the last major eruption, led to many fatalities for humans and cattle. Nowadays, the local government developed the "sister village" strategy for mitigation. That means cooperation within or between the local community has been constructed to provide shelter, logistics, and other disaster-related services. In this scenario, the meeting area and shelter have been coordinated. However, people's behavior has not been fully considered yet in the vulnerability assessment and government's contingency plan. On the other hand, evacuation issues in a volcanic disaster such as difficulty in expecting evacuation period, aging population, missed communication and risk perception, limited private vehicles in the community, and limited evacuation transport and supporters by the government need to be addressed for better mitigation. This situation led some people to walk to the meeting area, and low walking speeds by vulnerable persons may increase the risk and delay during an emergency.
The objective of this study is to find the effectiveness of the evacuation process, especially for the vulnerable community in the Mount Merapi area. Especially, this study purposes to develop a “mutual assistance” model for vulnerable people in the affected regencies with the people’s behavior and vehicle ownership as a viewpoint. The first goal is an assessment of the mutual assistance strategy and social vulnerability index (SoVI) of pedestrian evacuation. I conducted the surveys and then analyzed the data using a multicriteria method to obtain the SoVI values for communities. The second goal is the development of the assembly model to support safer and faster evacuation for vulnerable people. The AnyLogic software was selected for model simulation using input parameters from field surveys.
In conducting a survey, I measured the walking speed directly of the evacuation drills in four affected regencies. I also investigated the people’s behavior and eruption characteristics using an interview process with stakeholders and group discussions with local communities. After that, I used the multicriteria method and focused on two factors, social and age structure (young, vulnerable, and mutual assistance between them), and risk perception (work, rain, night, alert, and evacuation map). The index reflects the distribution of actual walking speed, mutual assistance, and the government's plan. The result showed that mutual assistance groups have a higher walking speed than vulnerable people but lower than young people. Mutual assistance coordination is crucial to support the vulnerable in shorter evacuation times. The social and age structure of the social vulnerability index has a stronger risk influence than the perception factor in the evacuation process.
The successful evacuation of vulnerable people during emergencies is a significant challenge. In this study, a mutual assistance strategy is proposed to support vulnerable people by evacuating them with young people. This strategy was simulated using AnyLogic software with the agent-based model concept. Pedestrians and vehicles played the roles of significant agents in this experiment. Evacuation departure rate, actual walking speed, group size, route, and coordination were crucial agent parameters. Residents’ attitudes, distribution of each agent, and actual walking speed were obtained from surveys. Then, I developed three scenarios and three models for the evacuation process. Scenarios considered traffic conditions of evacuation routes and models represented behavior approach. The results revealed that this mutual assistance model is effective for the rapid evacuation and risk reduction of vulnerable communities where successful evacuation rates have improved. As for mutual assistance behavior, Model 3, where young people are matched with vulnerable people in advance, has shown better results than Model 2. Additionally, Scenario C, where pedestrians have separate lanes from vehicles during the evacuation process, has resulted in more number of vulnerable people reaching the shelter than Scenario B in Model 3. The highest arrival rate was obtained by the combination of scenario C and Model 3. These findings are a novelty in the volcano context and reflect all categories of vulnerable behavior involving the elderly, disabled, children, and pregnant mothers. The model will benefit disaster management studies and authorities’ policies for sustainable evacuation planning and aging population mitigation.

Creators Faizul Chasanah

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