A validation data-set and suggested validation protocol for ship evacuation models

An evacuation model validation data-set collected as part of the EU FP7 project SAFEGUARD is presented. The data was collected from a cruise ship operated by Royal Caribbean International (CS). The trial was a semi-unannounced assembly trial conducted at sea and involved some 2500 passengers. The trial took place at an unspecified time however, passengers were aware that on their voyage an assembly exercise would take place. The validation data-set consists of passenger; response times, starting locations, end locations and arrival times in the assembly stations. The validation data were collected using a novel data acquisition system consisting of ship-mounted beacons, each emitting unique Infra-Red (IR) signals and IR data logging tags worn by each passenger. The results from blind simulations using maritimeEXODUS for the assembly trial are presented and compared with the measured data. Three objective measures are proposed to assess the goodness of fit between the predicted model data and the measured data

Investigating the impact of culture on evacuation response behaviour

The aim of this work was to investigate whether social culture impacts how people respond to an evacuation alarm. As part of this work four unannounced library evacuations were conducted in the Czech Republic, Turkey, Poland and the UK. In an attempt to isolate social culture as the primary independent variable across the trials, the key parameters that are known to influence Response Phase behaviour and performance e.g. population demographics, type of structure, alarm system, etc were controlled across the trials. Response Phase behaviour was determined for a total of 477 individuals, 192 from Poland, 51 from Turkey, 70 from the Czech Republic and 104 from the UK. The results suggest that there are significant differences in the nature of the population behaviour during the Response Phase across the four trials. On average, the population with the quickest to the slowest response times are: Turkey, Poland, UK and Czech Republic. When applied to a simulated evacuation, the observed differences in response time distribution for the national groups resulted in significantly different evacuation performance

Recommendations on the nature of the passenger response time distribution to be used in the MSC 1033 assembly time analysis based on data derived from sea trials

The passenger response time distributions adopted by the International Maritime Organisation (IMO)in their assessment of the assembly time for passanger ships involves two key assumptions. The first is that the response time distribution assumes the form of a uniform random distribution and the second concerns the actual response times. These two assumptions are core to the validity of the IMO analysis but are not based on real data, being the recommendations of an IMO committee. In this paper, response time data collected from assembly trials conducted at sea on a real passanger vessel using actual passangers are presented and discussed. Unlike the IMO specified response time distributions, the data collected from these trials displays a log-normal distribution, similar to that found in land based environments. Based on this data, response time distributions for use in the IMO assesmbly for the day and night scenarios are suggeste

Trapped on the seashore, seaborne evacuation, and impact of exposure to PM2.5: Live demonstration of the urbanEXODUS large-scale evacuation model

Wildfires can trigger large-scale pedestrian, vehicle and seaborne evacuations, and cause injuries and fatalities. Evacuation models are employed to better understand the involved processes and their interactions. During the final exercise of the European Commission’s H2020 IN-PREP project, urbanEXODUS was used within a training platform, by incident managers, to aid their response to a simulated disaster. The scenario involved a traffic accident escalating to a wildfire, causing the local community to evacuate. The model combined pedestrian and vehicle evacuation, and through a flow model, a simplistic representation of boat evacuation. The effects of wildfire on escape routes and possible fatalities were evaluated using fire perimeter data. The development of a novel fractional dose model allowed the software to determine agents’ acute exposure to PM2.5, in relation to the WHO daily mean Air Quality Guidelines (AQG). The simulation results comprise key evacuation performance parameters including evacuation times, fatalities, and escape route usage. Results indicate that 6% of the population was unable to leave the area and are treated as fatalities. The road network and boats were used by 69% and 31% of the evacuees respectively. PM2.5 exposure was zero for 84% of the evacuees, and below the AQG, for 1%, while 15% received, on average, a dosage of 7.6 times the AQG (range 1.0 – 28.3, SD = 5.8), which may cause respiratory and cardiovascular disorders. The model offers detailed evacuation information that is practically impossible to obtain otherwise, allowing crisis managers to take risk-informed decisions when planning for a crisis

The simulation of urban-scale evacuation scenarios: Swinley forest fire

Forest fires are an annual occurrence in many parts of the world causing evacuation of nearby residential areas and industrial facilities. The frequent occurrence of these events deems it necessary to develop appropriate evacuation plans for areas that are susceptible to forest fires. A well-established and well-validated evacuation model, buildingEXODUS, has been extended to model large scale urban/rural evacuations by including the road network and open spaces (e.g. parks, green spaces and town squares)along with buildings. The evacuation simulation results have been coupled with the results of a forest fire spread model and applied to the Swinley forest fire. Four evacuation procedures differing in the routes taken by the pedestrians were simulated and analysed providing key evacuation statistics such as time to reach the assembly location, the distance travelled and congestion experienced by the agents. In addition, the safety margins associated with using each evacuation route are identified. This is the time available between the safe passage of the pedestrians through the route and the route being considered no longer safe for pedestrian use. A key finding of this work is the importance of formulating evacuation procedures in response to wildfires by providing occupants timely evacuation notice and appropriate choice of routes to keep them at a safe distance from the fire even at the cost of taking longer evacuation routes

The development of pedestrian gap acceptance and midblock pedestrian road crossing behavior utilizing SUMO

While there are several published studies for modelling pedestrian behavior at signalized crossings in SUMO, the behavior of pedestrians crossing a road at a location other than a designated crossing, has not been considered to date. This work looks at how to represent pedestrian agents selecting to cross a road at arbitrary locations along the length of the road. The pedestrian agents utilize a gap acceptance model that represents how a pedestrian decides when to cross a road, based on the frequency and speed of approaching vehicles, while considering the spacing between them. Furthermore, the gap acceptance model allows the pedestrians to choose to cross all lanes in one go, when safe to do so, known as Double Gap or one stage crossing. Alternatively, if an agent is identified as a risk-taker, they may choose to cross lane by lane, sometimes waiting in the middle of the road, known as Rolling Gap or risk-taker crossing behavior. The inclusion of these two crossing behaviors allows for situations where urgency plays an important role in behavioral decision making, such as in emergencies, rush hour or in crowd management events. The outlined pedestrian crossing model is attained by integrating the pedestrian model EXODUS with SUMO, via the TraCI API

Trapped on the seashore, seaborne evacuation, impact of exposure to PM2.5: demonstration of the urbanEXODUS evacuation model

The 2021 wildfire season affected large communities in over ten countries around the Mediterranean basin consuming an area almost double the area burnt by wildfires over the past twelve years. In many cases, people were exposed to hazardous combustion products that caused mass multimodal evacuations, including pedestrian, vehicle, and seaborne evacuations as well as a large number of fatalities. Evacuation modelling can be used to better understand the processes involved, including the interactions between those processes. Such a model is urbanEXODUS, utilised during the final exercise (FSX3) for the European Commission’s Horizon 2020 project IN-PREP. The tool was used as part of a training platform for incident managers in collaborative response to large scale disasters. The scenario deployed during the FSX3, and presented in this work, involved a traffic accident and cascading effects that start a wildfire at a forested area, initiating a multi-modal evacuation of the local community. The model, able to simulate multi-modal evacuations, includes pedestrian and vehicle evacuation, and through the development of a flow model, a simplistic representation of boat evacuation. The model is also able to determine the effect of wildfire products using two different datasets that include (a) wildfire perimeter data and (b) smoke plume data that include PM2.5 concentration levels. The former limits the escape routes, causing engulfment and fatalities. The latter, through the development of a novel fractional dose model, determines the acute exposure of agents to PM2.5 in relation to the World Health Organisation (WHO) daily mean Air Quality Guidelines (AQG). The model demonstrates key evacuation performance results, including evacuation times, escape route usage and number and locations of fatalities. The results indicate that 6% of the entire population were unable to leave the area and are considered as fatalities. With regard to the evacuees, 69% utilised the road network to leave the area, while 31% utilised the seaborne evacuation. Exposure to PM2.5 was zero for 84% of the evacuees, while for 1% it was less than the AQG. However, 15% of the agents received a dosage of PM2.5 on average of 7.6 times the AQG (range 1.0 – 28.3, SD = 5.8). This level of exposure is expected to cause health problems including respiratory, cardiovascular and cerebrovascular disorders. The model offers detailed evacuation information that is practically impossible to obtain otherwise, allowing crisis managers to make risk-informed decisions when planning for a crisis

Evaluating the effectiveness of an improved active dynamic signage system using full scale evacuation trials

Emergency exit signs form an essential part of building wayfinding systems. However, in some emergency evacuation situations many people fail to see the emergency exit signs and in some cases, even if detected by the population, the signs have been ineffective in leading them to safety. These failings are primarily due to their inability to attract the immediate attention of the people they are there to assist and their lack of an ability to respond to a changing threat environment. The need for exit signs that attract attention when they need to be conspicuous, to redirect people to not just an exit route, but a viable and if possible an optimal exit route in an evolving emergency has driven the development of a new generation of advanced signage system, the Intelligent Active Dynamic Signage System (IADSS). The IADSS, developed as part of the European Commission FP7 funded GETAWAY project, attempts to meet these needs through the development of a novel Active Dynamic Signage System (ADSS) which can be controlled by an intelligent decision support system. This paper presents results that refine the effectiveness of the ADSS. When an exit route is considered non-viable, the adapted ADSS provides not only negative information i.e. that an exit is no longer available, but also positive information, i.e. directing the population to an alternative exit. In addition, in situations where a voice alarm system is used in conjunction with the ADSS, it is also important to ensure that the messaging does not potentially contradict the intent of the ADSS. The improved ADSS was tested in full-scale evacuation trials in a rail station. The trials suggest that the improved ADSS with voice alarm messaging that does not contradict the signage system successfully redirected 66% of the participants to the intended exit

Evacuation modelling for rapid multi-hazard tabletop exercise deployment

To prepare for large-scale emergencies and crisis affecting communities, authorities, and emergency commanders use several types of training methods ranging from seminars to full-scale exercises. Within this continuum of exercise types, tabletop exercises (TTXs) are habitually used to familiarise participants with mitigation strategies, population management and evacuation procedures conducted as a response to natural or technological hazards. Commonly, TTXs are paper-based, and if computerised, use basic electronic maps, tend to be scripted and have a linear nature. Information flow is unidirectional as the script dictates how the exercise unfolds. These exercises have little capacity for producing qualitative or quantitative feedback related to the impact that the received scenario injects (i.e., incoming messages including scripted events and hazard locations), the authorities’ decisions, and the impact of hazards have on the wellbeing of the community and the evacuation process. While informative during training, this type of feedback may prove vital in assessing the likely impact of real incident. In this work an evacuation simulation model is proposed to augment the TTX experience in real time, offering feedback and insights on the impact that such injects, decisions and hazards have on the simulated community. The proposed methodology is utilised in an actual TTX co-organised and executed by the Municipality of Rhodes, Greece, where the evacuation model is used to (a) develop the standard, non-incident specific evacuation procedures for the Medieval City of Rhodes (MCR), (b) to adapt these procedures based on the injects (generated on-site or telecommunicated, emulating receipt from the field), producing the TTX scenario and (c) to provide information on the impact that the TTX hazards have on the evacuation process. The integration of evacuation modelling into the TTX process demonstrated that it is possible to gain a deeper understanding of the complexities related to route choices in response to path closures, the assembly and evacuation performance, as well as the management of the simulated incident by analysing qualitative and quantitative simulation results

Towards Budget Comparative Analysis: The Need for Fiscal Code Lists as Linked Data

ABSTRACT Code lists are a key part of budget datasets as they serve for the coding of fiscal concepts within them. However, the great diversity of classifications across countries and concepts does not allow to presume upon their actual value, as dimension properties. In this paper we discuss the need for creating code lists Linked Data for the classifications used in fiscal datasets, in three basic steps. First, code lists have to be extracted from fiscal datasets, especially if there are no relevant metadata in the budget description, which could easily identify them. Next, code lists from different datasets or sources have to be represented in the same way, with SKOS vocabulary, thus they can be linked with each other. Finally, linking of similar code lists will also allow the linking of the containing datasets, increasing their data analysis and knowledge extraction possibilities