Effective Evacuation Routes Research Articles

Robust Estimation of Crowd Density Using Vision Transformers

Estimating and predicting crowd density at large events or during disasters is of paramount importance for enhancing emergency management systems. This includes planning effective evacuation routes, optimizing rescue operations, and ensuring efficient deployment of emergency services. Traditionally, surveillance systems that rely on cameras have been employed to monitor crowd movements. However, accurately estimating crowd density using such systems presents several challenges. These challenges stem primarily from the interaction between large crowds and the limitations of two-dimensional cameras in capturing the full scope of three-dimensional spaces. Optical distortions, environmental factors, and variations in camera angles further complicate the task, making accurate estimations difficult to achieve. To address these challenges, this paper introduces a robust method for calculating crowd density that leverages advanced vision transformers. By combining the output of these transformers with a two-stage neural network, the method effectively mitigates the limitations of traditional approaches. One of the key advantages of the proposed system is its robustness, which allows it to perform well across different camera specifications, installation locations, and image aspect ratios. The method applies and evaluates various deep learning techniques, introducing improvements to existing network structures that are better suited for the problem at hand. Extensive experimental verification demonstrates that the proposed method consistently produces accurate crowd density estimates, even in diverse and complex crowd environments. This robust performance underscores its potential for improving emergency management and crowd control in real-world situations.

Analysis and Geovisualization of Tsunami Hazard and Evacuation Routes in the Opak-Progo Coastal Area

The southern coastal area of Java has a high risk of tsunamis. Additionally, the presence of rivers flowing in the south of Java Island poses a greater tsunami threat because these rivers can act as "toll roads" for tsunami waves to enter the land. Therefore, this study was conducted in the coastal area of the Opak-Progo watershed to determine the level of tsunami hazards and plan effective evacuation routes. The hazard map was created using the Berryman method, which employs parameters such as slope, surface roughness coefficient, coastline, and tsunami run-up height scenario; a 3-metre scenario was used in this study. Network analysts also determined evacuation routes using the nearest facility method. Network analysis was used to identify an optimised route with four evacuation sites. This research has the potential to significantly contribute to tsunami mitigation and evacuation planning in the coastal areas of the Opak-Progo watershed.

Network analysis for determining the fastest evacuation routes in flood-prone areas of the Tuntang Watershed, Indonesia

Flooding in the Tuntang Watershed, Central Java Province, is a hydrological disaster that occurs regularly. Several factors, such as high rainfall, limited water catchment areas, and narrowing riverbanks, cause flooding. The amount of material and non-material losses can be minimized through an effective disaster mitigation process. One way is to determine and establish flood evacuation routes to shelters. This research aims to analyze the fastest and most effective evacuation route for residents using Geographic Information Systems. This research process includes analyzing flood-prone areas, ranging from highly vulnerable areas to areas that are not vulnerable. Furthermore, it analyzes population density, distribution of residential areas, natural physical conditions, and road conditions and identifies the location of the best evacuation center for residents affected by flooding. The method used is Sample Additive Weighting (SAW) to determine the best evacuation point and Network Analysis Fastest Route to determine the optimal evacuation route to the designated evacuation center. The results of this study include modeling a flood evacuation route with an estimated effective evacuation time of 30-45 minutes, consisting of 50 fastest alternative routes to appropriate shelters.

Tsunami Hazard Mapping and Evacuation Path Determination using field Survey and Geographical Information Systems at Widarapayung Wetan, Cilacap

In 2006, a tsunami hit Pangandaran, and its effects were felt in Cilacap. There were 664 fatalities, 498 injuries, and 55 million dollars in damages, and 1623 homes were destroyed or severely damaged due to the tsunami. Furthermore, the village of Widarapayung was among those devastated by the tsunami, which reached a height of up to 5 meters and claimed the lives of 12 people. In addition, Widarapayung is a popular tourist destination and one of the venues for 2019’s professional surfing events. Therefore, disaster prevention measures are essential to lessen the impact of disasters and save lives. The objective of this study is to assess the vulnerability of the Widarapayung Wetan area to a tsunami and make recommendations for evacuation routes and regional infrastructure development to reduce casualties and damage. This research utilized COMCOT to model the megathrust segment with a possible magnitude of 8.7, with worst-case values acquired from the catalog PuSGeN 2017. Additionally, the data on topography and bathymetry collected by DEMNAS and BATNAS are utilized in this investigation. The modeling results indicated a 50-minute arrival time for the tsunami waves, a maximum run-up height of 14-18 meters, and a submerged area of roughly 4.57 km2. In addition, the most effective evacuation routes were determined by combining the outcomes of field surveys and Geographic Information System simulations. This research will provide local governments with helpful information for making informed decisions about infrastructure and spatial development in the future.

A Smart Evacuation Guidance System for Large Buildings

In large buildings, during the situation of fire or other hazards, a smart evacuation guidance system needs to fully consider manifold aspects of hazards to guide evacuees through exit gates as fast as possible by dynamic and safe routes. In this paper, we propose a smart evacuation guidance system with a dynamic evacuation routing approach by using the LCDT (Length-Capacity-Density-Trustiness) weighted graph model and partial view (PV) information which represents the hazard intensity and the crowd congestion information of a group of sections/floors in the building. The proposed system is designed as a distributed system with multiple layers of computing by using smart indicators. Given such a system, we develop an efficient distributed approach, so-called LCDT&PV, to find out effective evacuation routes dynamically. We then propose an estimating congestion strategy in order to improve the efficiency of dynamic evacuation routes. To validate the proposed system, we implement a simulator to compare the proposed evacuation routing approach with baseline approaches. Experimental results show that the proposed approach reduces up to 30% of the total evacuation time compared with others. Furthermore, through the results of initial smart indicator implementation, which can interact with the simulator, we show the viability of the proposed system.

Forest Fire Assessment Using Remote Sensing to Support the Development of an Action Plan Proposal in Ecuador

Worldwide, forest fires exert effects on natural ecosystems, contributing to economic/human losses, health effects, and climate change. Spectral indices are an essential tool for monitoring and analyzing forest fires. These indices make it possible to evaluate the affected areas and help mitigate possible future events and reduce damage. The case study addressed in this work corresponds to the Cerro of the Guadual community of La Carolina parish (Ibarra, Ecuador). This work aims to evaluate the degree of severity and the recovery of post-fire vegetation, employing the multitemporal analysis of spectral indices and correlating these with the climatological aspects of the region. The methodological process was based on (i) background information collection, (ii) remote sensing data, (iii) spectral index analysis, (iv) multivariate analysis, and (v) a forest fire action plan proposal. Landsat-8 OLI satellite images were used for multitemporal analysis (2014–2020). Using the dNDVI index, the fire’s severity was classified as unburned and very low severity in regard to the areas that did not regenerate post-fire, which represented 10,484.64 ha. In contrast, the areas classified as high and very high severity represented 5859.06 ha and 2966.98 ha, respectively. In addition, the dNBR was used to map the burned areas. The high enhanced regrowth zones represented an area of 8017.67 ha, whereas the moderate/high-severity to high-severity zones represented 3083.72 ha and 1233.49 ha, respectively. The areas with a high severity level corresponded to native forests, which are challenging to recover after fires. These fire severity models were validated with 31 in situ data from fire-starting points and they presented an accuracy of 99.1% in the high severity category. In addition, through the application of principal component analysis (PCA) with data from four meteorological stations in the region, a bimodal behavior was identified corresponding to the climatology of the area (dry season and rainy season), which is related to the presence of fires (in the dry season). It is essential to note that after the 2014 fire, locally, rainfall decreased and temperatures increased. Finally, the proposed action plan for forest fires made it possible to define a safe and effective evacuation route to reduce the number of victims during future events.

Tsunami Hazard Zone and Multiple Scenarios of Tsunami Evacuation Route at Jetis Beach, Cilacap Regency, Indonesia

The 2006 tsunami, throughout the Pangandaran to Cilacap Coast, resulted in 802 deaths and 1623 houses being destroyed. At Jetis beach, Cilacap Regency, 12 people died, and hundreds of houses were damaged. This area is a tourism destination, visited by hundreds of people per week. Therefore, this study aims to determine a tsunami hazard zone and the most effective evacuation route based on multiple factors and scenarios. The method of this study includes scoring, weighting, and overlaying the distance of the Jetis beach from the shoreline and the river, including the elevation and topography. The study results depict five levels of tsunami hazard zone at the Jetis beach: an area of high potential impact, moderately high, moderate, moderately low, and low. The southern Jetis beach is the most vulnerable area with regard to tsunamis, characterized by low elevation, proximity to the beach and rivers, and gentle slopes. The simulation results show the four fastest evacuation routes with the distance from the high-risk zone to the safe zone of around 683–1683 m. This study infers that the southern part of the Jetis beach, in the moderate to high impact zone, needs greater attention as it would suffer worst impact from a tsunami.

Evaluation of the Dimensions of the Tsunami Evacuation Path for the Community of Air Tawar Barat Village, North Padang District, Padang City, Based on Geographic Information System (GIS)

Air Tawar Barat Village is located in North Padang District, Padang City which is directly adjacent to the Indian Ocean in the west, so there is a risk of a tsunami disaster. The current evacuation route, which is one of the efforts to overcome the tsunami disaster, seems to be still ineffective to use because the distance that must be covered is 3-5 km in less than 30 minutes. This study aims to determine the direction of an effective evacuation route and then make a comparison with the evacuation route that has been determined by the Government. The method used is Network Analyst. The results of this study obtained 3 alternatives to make evacuation more effective. The alternative is to make access roads around Jalan Gajah to go to P-TES in the UNP area. Alternative 2 is to make P-TES in the parking lot of the Air Tawar Health Center so that people around the river mouth can evacuate faster because they are closer. Alternative 3, the community around the North Padang Police Sector can evacuate by heading to P-TES on Jalan Polonia, Air Tawar Timur Village to stay away from the beach. The three alternatives make the evacuation time to 10 minutes by heading to 26 P-TES. In addition, the evacuation map as a result of the analysis is more effective because the route has a route that is more likely to be taken by the community compared to the government evacuation map.

Route recommendation for evacuation networks using [formula omitted] queueing models

While natural disasters such as hurricanes, tsunamis, and earthquakes are inevitable, improving existing emergency response approaches and technology becomes critical in today’s smart city development. That is, ensuring evacuees get a fast and effective evacuation route plays a very important role in increasing survival rate and reducing damage during emergency or disaster situations for smart cities. In this research, we investigate the design and development of efficient evacuation routes. By considering the realistic response to emergency evacuations, we present a model based on the number of incoming vehicles in different periods of time. In this paper, we propose a Queueing-based Recommendation system (Q-Recomm) for dynamic route recommendations for evacuees to use at the time of a disaster. Compared with other existing studies that use static conditions, our proposed algorithms consider dynamic road conditions by using queueing theory and graph theory. Specifically, we first characterize the evacuation network of a disaster as a directed acyclic graph and then exploit an MMPP/M/1/N queueing model to derive the optimal route in terms of the minimum driving time by analyzing road congestion, vehicle wait time, and road capacity as well as vehicle arrival rates for chosen routes, using high-end sensors for dynamic data acquisition. We propose the Queueing-based Time Constrained Route Recommendation (Q-TCRR) algorithm and the Queueing-based Minimum Driving Time Route Recommendation (Q-MDTRR) algorithm for route recommendation in evacuation networks. Our experimental results validate the accuracy of Q-TCRR and Q-MDTRR, respectively, and we also demonstrate that the Q-MDTRR algorithm has a lower driving time compared with both MacroServ and the shortest path route based on Dijkstra. Thus, while edge computing in vehicular ad hoc networks becomes a promising solution for evacuation networks, our two proposed algorithms can be flexibly realized in edge computing in vehicular ad hoc networks due to their computational efficiency.

Crowd Evacuation Simulation Research Based on Improved Reciprocal Velocity Obstacles (RVO) Model with Path Planning and Emotion Contagion

Crowd evacuation simulation is an important research topic for designing reasonable building layout and effective evacuation routes. The reciprocal velocity obstacles (RVO) model is a pedestrian motion model which is used, but it does not work when complex and multiple obstacles are present in the scene. This paper proposes an improved RVO model with path planning and emotion contagion for crowd evacuation simulation. The model uses the vertices of the obstacles to construct pedestrian path nodes for planning pedestrian evacuation paths. To make the pedestrian evacuation paths simulation results more reasonable, the safety and congestion of the path nodes are considered, to plan the shortest evacuation path. Finally, a contagious disease model is introduced to study the impact of emotion contagion on the evacuation process. A crowd evacuation simulation system is developed, and simulations have been carried out in a variety of scenarios. Experiments show that the model can effectively simulate crowd evacuation, providing a powerful reference for building and layout design.

Participatory Mapping of Tsunami Evacuation Routes (Case Study of Karangbenda Village Cilacap Regency)

Indonesia is one of the countries with a high tsunami risk, in this case the community plays an important role in disaster management, one of which can be done through the preparation of a tsunami evacuation route map which can be done through participatory mapping. This research was conducted in Karangbenda Village, Adipala District, Cilacap Regency, the purpose of this study was to determine how the skills of the community in determining tsunami evacuation routes were compared with the criteria for evacuation locations and effective evacuation routes and to test the effectiveness of tsunami evacuation routes prepared by the community. Data collection in this study was carried out through focus group discussions (FGD) and field surveys. The results show that the community can arrange a tsunami evacuation route properly, the evacuation route consists of the evacuation location and evacuation route, the designated evacuation location is in accordance with the evacuation location criteria and the evacuation route is in accordance with the route obtained through network analysis. The effectiveness level of the tsunami evacuation route was 98.82% and there were some people who were unable to reach the evacuation location within the specified time, totaling 36 people who were in the area of Dusun Congot to be precise in RT 02 / RW 02 because of the long distance from the evacuation location.

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

A safe and effective evacuation route is important for reducing casualties during building fires, and this topic has been a long-term focus of emergency management. Indoor space is a space within one or multiple buildings consisting of architectural components and is the basis of indoor route analyses. Based on indoor space, an indoor network model is designed that considers fire protection design, spatial matching between fire information and the indoor space, and the passability of the indoor space during a fire. Then, an evacuation route selection algorithm that considers hazard and time is proposed. The key features of the route selection algorithm, which include assessing the fire hazards, evacuation time in each indoor space and parallel computing in the route selection algorithm, are subsequently presented. Finally, taking a gymnasium as an example, case modelling and fire information integration are performed to investigate two fire scenarios and the optimal evacuation routes over time are identified in each scenario.

Three-Dimensional Indoor Fire Evacuation Routing

Traditional indoor navigation algorithms generally only consider the geometrical information of indoor space. However, the environmental information and semantic parameters of a fire are also important for evacuation routing in the case of a fire. It is difficult for traditional indoor navigation algorithms to dynamically find an indoor path when a fire develops. To address this problem, we developed a multi-semantic constrained three-dimensional (3D) indoor fire evacuation routing method that considers multi-dimensional indoor fire scene-related semantics, such as path accessibility, path recognition degree, and fire parameters. Our method enhances the navigation semantics of indoor space by extending the fire-related components of indoor model based on IndoorGML and integrating location semantics of IndoorLocationGML. We also propose quantifiable indoor fire-oriented routing semantics and establish a navigation cost function that evaluates semantic changes during a fire. We designed an indoor routing algorithm with multiple semantic constraints based on the A* algorithm. The indoor routing results were analyzed and compared in simulation experiments. The experimental results showed that the proposed model can remove unusable nodes and edges from the obtained navigation path and provides a safer and more effective evacuation route than traditional algorithms.

Simulating the dynamical features of evacuation governed by periodic vibrations

Abstract Emergency evacuation often occurs in extremely adverse environments, such as on a shaking floor vibrated by seismic waves or water waves, whereas present work seldom takes this into consideration. Thus, based on an improved social force model (SFM), the influence of wave-induced fluctuations on evacuation dynamics is investigated. The driven wave is simplified as a periodic sinusoid characterized by a peak value and period length. Intriguingly, fluctuations can substantially weaken the famous “faster-is-slower” effect. That is, trying to move faster, namely, increasing the desired velocity, always facilitates evacuation. Moreover, there exist combinations of moderate peak values and large period lengths, resulting in the minimum evacuation efficiency. It is also worth noting that the increment of extreme panic induces the “collapse” of social norms, which eventually leads to heavy casualties. Our work thus can provide insight into pedestrian dynamics in shaking environments and help plan effective evacuation routes.

Initiative evacuation routes for earthquake hazard in the active Opak fault (Sengon Village, Klaten, Central Java)

This research aimed to explain how the initiation process from the community reconstructs evacuation routes in high risk earthquake area. The study location took place in Sengon Village, Prambanan District, Klaten Regency. Sengon was located near Opak fault zone where experienced tremendous disaster in 2006. Since a decade, the mitigation infrastructure was very deficient. The community-based mitigation was not also available yet in this village. However, the community was highly potential to build disaster resilience since supports by the government. Route condition in Sengon was also greatly supportive to construct effective evacuation route. Based on identification and community planning, the evacuation route consisted of local road and tracking road. There were also found that eight places classified as secondary assembly shelters and two places classified as a primary evacuation shelter. The SWOT analysis was done for supporting the strategy to develop the evacuation infrastructure.

The analysis of Tsunami evacuation route based on geographic information system: a case study in the coast of Lampung Bay

The most fundamental issues for local people who are potentially at risk to tsunami threat are awareness and preparedness. The aim of this paper is to define the effectiveness of tsunami evacuation routes toward tsunami hazard along the coast of Lampung bay. The parameter applied in this study were elevation and slope created based on Aster GDEM while the coastline distance was made based on vector map and tsunami inundation obtained by Hills and Mader equation. In addition, the road network was derived from Development Planning Agency at Sub-National Level. AHP process was applied in determining the weight of the parameter by using pair-wise comparison via five normalized matrix iteration. Thus, there are five vulnerability classes that were classified. Weighted overlay through spatial analysis in geographic information system (GIS) was used in this study in order to make the final tsunami vulnerability map. The Network Analysis through Closest Facility Analysis in GIS was used to create the effective evacuation route and to point out 34 effective evacuation locations that could be reached by the people before the tsunami strikes. The results presented in this paper could eventually facilitate the improvement in the basic data for city planning related to evacuation process and management strategy during disaster.

Mathematical modeling approach of an evacuation model for tsunami risk reduction in bengkulu

In tsunami mitigation plan, evacuation plays a crucial measure for saving human lives, especially for communities who are living in coastal areas. The main problem of evacuation system is to minimize the time to evacuate the vulnerable population. This can be done by determining the effective evacuation route. The effective evacuation route from a cluster (center of population) to an assembly point (safety area) should consider the minimum travel time. In calculating travel time between cluster and assembly point we have to consider the speed of walking of evacuees. The speed of walking of evacuees is influenced by several factor i.e width of the road, road density, number of evacuees in a group, etc. This research develop a mathematical modeling to choose the most effective evacuation route in coastal areas of Bengkulu city, Indonesia. The used method in determined minimun travel time is Flyod Warshall algorithm and the tsunami evacuation system software is made using mathlab programming. Indonesian Tsunami Early Warning System (InaTEWS), takes about 15 minutes after an early warning tsunami to evacuate. The result of the evacuation modeling shows there are 5 clusters of 48 clusters need more than 15 minutes to reach safety area.

Tsunami Disaster Preparedness Simulation on North Buton Regency

Geographical location of North Buton Regency which directly opposite the Banda Sea and placed in the reverse fault of Makassar Strait, Matano fault, Lawanoppo, and Kolaka, which are tsunami-prone areas due to earthquake and submarine landslide. These then caused the area has high disaster risk, because of the settlement that is located on the seashore. Therefore, a study to understand the preparedness level of community in North Buton Regency in confronting the tsunami disaster is needed; in order to be able to determine the mitigation steps, also the effective evacuation route and location to minimize the casualties caused by tsunami. Kulisusu Sub-district is a territory with a fairly long coastal area, wherein the population density is the highest in North Buton Regency, this then made the area has high disaster risk. This research used questionnaire instrument to discover the preparedness level of the community, and the numerical simulation method with multi-agent system in the tsunami evacuation simulation. The conducted simulation did not specify the evacuation route or path, yet the agents were allowed to move freely to the shelter. The simulation was conducted at day and night time. The result of the research pointed on matter of preparedness level of community, in which factor of preparedness of the community in facing the disaster is very important, by the means of establishing simulation drill, preparing the controller officers, and managing the comfort on the shelter, such as strategic location and good position, also creating a good early warning system so that more residents could be saved.

Spatial modelling for tsunami evacuation route in Parangtritis Village

Tsunami is a series of huge sea waves that commonly occurs because of the oceanic plate movement or tectonic activity under the sea. As a sudden hazard, the tsunami has damaged many people over the years. Parangtritis village is one of high tsunami hazard risk area in Indonesia which needs an effective tsunami risk reduction. This study aims are modelling a tsunami susceptibility map, existing assembly points evaluation, and suggesting effective evacuation routes. The susceptibility map was created using ALOS PALSAR DEM and surface roughness coefficient. The method of tsunami modelling employed inundation model developed by Berryman (2006). The results are used to determine new assembly points based on the Sentinel 2A imagery and to determine the most effective evacuation route by using network analyst. This model can be used to create detailed scale of evacuation route, but unrepresentative for assembly point that far from road network.

Integrated optimization for shelter service area demarcation and evacuation route planning by a ripple-spreading algorithm

Shelter is one type of emergency facilities and plays a critical role in disaster response. In operation level, a shelter is the destination of post-disaster evacuation route, whose scientific service area demarcation can have a great positive influence on evacuation route planning. Effective evacuation route planning can also validate and support the service area demarcation of shelter. This study aims to optimize shelter service area demarcation and post-disaster evacuation route planning simultaneously in order to improve the efficiency of current shelter operation and further reduce disaster risk, which is seldom addressed before. We proposed an integrated optimization model for jointly solving shelter service area demarcation and evacuation route planning problems, which keeps contiguity of service areas, ensures an evacuation route within the same service district, shortens the evacuation route, satisfies capacity constraints and maintains integrity. To solve the problem, a ripple-spreading algorithm is adopted with combining contiguity and capacity operators. A real-world case study was conducted in the Chaoyang district of Beijing, China. A locally optimal scheme for service area demarcation and evacuation route planning was obtained with satisfying constraints as much as possible, which confirm the validity of ripple-spreading algorithm application in the joint problem.