Modelling and Simulating Indoor Pedestrian Movement Behaviour and Displacement

Inimeste evakuatsiooniteed on hoonete ülesehituse üks tähtsamaid osasid. Nii inimestele kui ka hoone omanikele tooks kasu, kui enne hoone ehitust oleks teada, kas evakuatsiooniteed on piisavalt efektiivsed. Inimeste kasu oleks nende elu ja hoone omanike kasu oleks kahjunõute puudumine vigastatud inimestelt või surnute lähedastelt. Inimeste liikumise simuleerimiseks kasutatakse üldiselt kolme erinevat meetodit: osakestepõhine lähenemine (ühiskondliku jõu mudel), mobiilsideautomaadi põhine lähenemine ja autonoomsed agendid. Kaks esimest meetodit on makroskoopilised mudelid ning viimane meetod on mikroskoopiline mudel. See lõputöö annab ülevaate arendatud mikroskoopilisest mudelist, mis kasutab autonoomseid agente, grupi mudelleerimist ning sotsiaalse võrdluse teooriat, et hinnata hoone väljapääsude disaini. Mikroskoopiliste mudelitega võib igal agendil olla erinevad omadused ning seosed läheduses asuvate inimestega (näiteks sõbrad ja pere). Inimesed kasutavad sotsiaalse võrdluse teooriat oma igapäevaelus, et end teistega võrrelda. Evakuatsiooni olukorras moodustavad sarnased inimesed, kasutades sotsiaalse võrdluse teooriat, gruppe ja mõjutavad üksteist. Mudel programmeeriti kasutades Pythonit, SUMO-t ja TraCI-t. Lõutöös tehtud simulatsioonid kasutavad näitena Ülemiste keskust, mis asub Tallinnas, Eestis. Erineva arvu väljapääsude ja inimeste vaheliste seoste jaoks viiakse läbi mitmeid simulatsioone. Tulemused näitavad, et mida kaugemal on väljapääsud üksteisest, seda väiksem on evakuatsiooni jaoks kuluv aeg. Samad tulemused saadi ka ainult ühe väljapääsuga ning kõikide väljapääsudega. Lähestikku asuvate väljapääsude juurde tekkivad kitsaskohad on põhjuseks ka pikematele evakuatsiooniaegadele. Kui uurida väljaspääsudest väljuvate inimeste jaotust, siis eelistavad agendid samuti üksteisest kaugemal asuvaid väljapääse. Inimeste kiirus ei mõjuta evakuatsiooniaegu nii palju, nagu alguses arvatud suurema arvu inimestega, kuna rahvahulga tihedus ei luba inimestel saavutada kiiremat kiirust. Viimane tulemus on see, et kiirustega 1.4 m/s ja 2.5 m/s suudab 200 inimesest 90\\% hoonest väljuda keskmiselt 400 sekundi jooksul. Selline tulemus tuli kõikide erinevate väljapääsudega. Viimased 10\\% võisid olla vanurid või segaduses inimesed, kes poole hoonega tuttavad. Järelikult on suurem osa turvaliselt hoonest väljunud 6 minuti ning 40 sekundiga, mis tundub 200 inimese puhul üpris reaalne tulemus. Arendatud mudelit saab kasutada hoone väljapääsude disaini hindamiseks enne hoone ehitamist. Selle mudeli kasutamine võib aidata kavandada paremaid evakuatsiooniteid, kuna kasutaja saab mudelile sisse anda erinevate hoonete plaane.Pedestrian evacuation routes are an important part of building's architecture. Knowing before building a structure if the evacuation routes are efficient enough should benefit both the people and the owners of the building. One's benefit is their life, the other's benefit not paying hospital and other fees for the injured or deceased. Three different approaches of pedestrian simulations are mostly used - particle-based approach (social force model), CA-based approach, and autonomous agents. The two first approaches are macroscopic models and the latter is a microscopic model. This thesis gives an overview of an implemented microscopic model, which uses autonomous agents, group modelling and social comparison theory to evaluate building egress design. With microscopic models each agent can have different attributes and ties with other people in the vicinity (e.g. friends and family). People use social comparison theory (SCT) in their daily lives to compare themselves to others. In an evacuation situation similar people form groups by social comparison theory and influence each other. The model is implemented using Python, SUMO and TraCI. In this thesis a case study is done on Ülemiste center in Tallinn, Estonia using the implemented model. Different number of exits and pedestrians are tested to see how they are associated. The results show that the farther apart the exits are, the smaller the evacuation times are. The same results appears with only one exit and all exits. Bottlenecks near the exits closer together are the reason for higher evacuation times. Agents also prefer exits farther apart when analysing the distribution between exits. Speed does not affect the evacuation time as much as expected with higher number of pedestrians because the density of the crowd disallows the agents to reach their high speed. The final outcome is that with speeds 1.4 m/s and 2.5 m/s 90\\% of people out of 200 agents exit the building around 400 seconds. This kind of result happened with all exit configurations. The other 10\\% might be older or confused people who are not familiar with the building's floor plan. Majority of people are, therefore, safe in 6 minutes and 40 seconds, which seems quite realistic for 200 people. The model implemented can be used to assess and evaluate a building's egress design before the structure is actually built. It can help design better evacuation routes for buildings because a user-specified floor plan can be used by the model

Panic That Spreads Sociobehavioral Contagion in Pedestrian Evacuations

Crowds are a part of everyday public life, from stadiums and arenas to school hallways. Occasionally, pushing within the crowd spontaneously escalates to crushing behavior, resulting in injuries and even death. The rarity and unpredictability of these incidents provides few options to collect data for research on the prediction and prevention of hazardous emergent behaviors in crowds. This study takes a close look at the way states of agitation, such as panic, can spread through crowds. Group composition—mainly family groups composed of members with differing mobility levels—plays an important role in the spread of agitation through the crowd, ultimately affecting the exit density and evacuation clearance time of a simulated venue. This study used an agent-based model of pedestrian movement during the egress of a hypothetical room and adopted an emotional, cognitive, and social framework to explore the transference and dissipation of agitation through a crowd. The preliminary results reveal that average group size in a crowd is a primary contributor to the exit density and evacuation clearance time. The study provides the groundwork on which to build more elaborate models that incorporate sociobehavioral aspects to simulate human movement during panic situations and account for the potential for dangerous behavior to emerge in crowds

Modeling of Household Evacuation Decision, Departure Timing, and Number of Evacuating Vehicles from Hurricane Matthew

This dissertation investigates households’ evacuation decision, number of household vehicles used in evacuation, and departure timing from Hurricane Matthew. Regarding the evacuation decision, this dissertation takes a step further by presenting three level evacuation decision models that include full, partial, and no evacuation alternatives rather than the binary evacuate/stay decision. Multinomial (MNL) regression and random parameter MNL techniques were utilized to develop the prediction models. Results showed that some of the variables which affect the evacuate/stay decision have different influences on the three alternatives. The preferred MNL model was tested for random parameters and one random parameter (age of the respondent) was identified for the utility expression pertaining to the no evacuation alternative. For the vehicle choice study, zero truncated Poisson regression was utilized with the survey data. This modeling approach has rarely been applied to the evacuation context and the prediction of the number of household vehicles used is relatively understudied, compared to other evacuation-related decisions. The final preferred model contains three significant variables (marital status, gender, and evacuation timing from 6 am to noon). The final part of this dissertation investigates the factors affecting departure timing choice. Having an accurate estimate of the departure time will allow the prediction of dynamic evacuation demand and developing effective evacuation strategies which will enhance the overall evacuation planning and management. A Cox proportional-hazards model was utilized to model the evacuation departure timing. Four significant variables were identified in the final model, two of them are related to uncertainty. This part of the dissertation also studies evacuees’ stated preference about whether or not they would change their evacuation timing if they relived the hurricane event. In our study, almost 34% of respondents reported that they would change their departure timing if they relived the hurricane event. A binary logit model was utilized in this part and the preferred model contains five significant variables related to past experience, the type of evacuation order received, and the evacuation destination