Research on Evacuation Path Planning Based on Improved Sparrow Search Algorithm

Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Firstly,the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm.Secondly,the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima.Finally,the local search mechanism based on the mountain climbing method was incorporated into the local search stage of the SSA algorithm,improving its local search ability.To evaluate the effectiveness of the proposed algorithm,the Whale Algorithm,Gray Wolf Algorithm,Improved Gray Wolf Algorithm,Sparrow Search Algorithm,and MSSA Algorithm were employed to solve various test functions.The accuracy and convergence speed of each algorithm were then compared and analyzed.The results indicate that the MSSA algorithm has superior solving ability and stability compared to other algorithms.To further validate the enhanced algorithm’s capabilities for path planning,evacuation experiments were conducted using different maps featuring various obstacle types.Additionally,a multi-exit evacuation scenario was constructed according to the actual building environment of a teaching building.Both the sparrow search algorithm and MSSA algorithm were employed in the simulation experiment for multiexit evacuation path planning.The findings demonstrate that the MSSA algorithm outperforms the comparison algorithm,showcasing its greater advantages and higher application potential.

Evaluating human behaviour during a disaster evacuation process:A literature review

The frequency of natural and man-made disasters has increased over the past few decades,which has doubled the significance of evacuation planning because it directly affects people’s lives and properties.How evacuees behave during a disaster and the methodologies to assess their behaviour are vital factors in managing any emergency scenario.For example,during the evacuation of a transportation network,users’amount of information and how they react are imperative to achieve a resilient response to a disaster.Even though there are numerous approaches for assessing evacuee behaviour,further research is needed to determine how and when each methodology should be employed.This paper intends to evaluate and classify the methodologies that have been presented up to date to create a more consistent approach to interpreting human behaviour during an evacuation process.The majority of studies focus on how people behave during an evacuation of a building,with less attention paid to how they behave during a transport evacuation.Among the proposed methodologies in this paper,the virtual reality approach,in individual behaviour,and agent-based models,in crowd behaviour,have more advantages than other approaches.Overall,a comparison between the proposed approaches is made in the discussion part.The output of this study provides the classifications and suggestions for researchers to pick an appropriate approach based on the types of problems,and some direction for future studies are introduced.To reach the research goal,177 papers have been reviewed between 1954 and 2022.

A Study on the Methods for Estimating the Distribution of Pedestrians in an Underground Mall by Use of Watch Cameras

This paper shows the method of estimating spatiotemporal distribution of pedestrians by using watch cameras. We estimate the distribution without tracking technology, with pedestrian＇s privacy protected and in Umeda underground mall. Lately spatiotemporal distribution of pedestrians has being increasingly important in the field of urban planning, disaster prevention planning, marketing and so on. Although many researchers have tried to capture the information of location as dealing with some sensors, some problems still remain, such as the investment of sensors, the restriction of the number of people who has the device they are able to capture. From such background, we develop an original labelling algorithm and estimate the spatiotemporal distribution of pedestrians and the information of the passing time and the direction of pedestrians from sequential images of a watch camera.

Evacuating a First Nation Due to Wildfire Smoke:The Case of Dene Tha’ First Nation

Almost every year,First Nations are evacuated in Canada because of wildfire proximity and smoke.Dynamics of wildfires,and remote locations,unique sociocultural characteristics,and limited emergency management resources present challenges for evacuation organizers and residents.This study explores how Dene Tha’First Nation evacuated their Tachécommunity in July 2012 due to wildfire smoke and how the evacuation process affected evacuees.Interviews were completed with 31 evacuation organizers and residents to examine the factors that helped and hindered the evacuation process.Lack of information about the nearby wildfire,smoke,and evacuation of the nearby small community of Zama City,combined with a generic evacuation plan,delayed and posed challenges during the evacuation of this Dene Tha’community.Strong leadership and its role in community organizing,keeping families together,providing the social support they needed,and using familiar host communities,demonstrated and contributed to the community’s resilience during the evacuation.Measures to improve evacuations and emergency management in the community and other First Nations in Canada are identified and discussed.