Massive population evacuation in an urban context

International audienceIncreasing urban sprawl all over the world leads to an increase of vulnerabilities, as greater numbers of goods and people are exposed to hazards, both natural (flood, quakes, fires, tsunami, epidemic) and industrial (factories, plants). Population evacuation features amongst the tools political managers can use to mitigate these risks. When evacuations are decided, managers must strike a fine balance between displacing all the people needed to avoid injuries and fatalities, and not evacuating people that would finally not be struck by the hazard. Evacuated populations convoys must furthermore not lead to a sub-crisis where they become new vulnerabilities, or through disorder and density prevent the management of other vulnerabilities. There is regretfully a scarcity of tools to help risks manager make this kind of decision. We present here our works on such tools. Most risk management policies focus on a planar, continuous conception of space. Seveso Directives for example use different radius around the hazard center, a plant for example, to find which housings and business will be affected at which degree. We described in our presentation for UrbanNet 2013 how this approach was found lacking for handling road networks, both as vulnerabilities of the direct hazard, and as the means for a successful crisis management. In order to overcome this obstacle we proposed a city-wide agent based simulation called MOSAIIC to model the car traffic, both in normal and extraordinary situations. In MOSAIIC each driver is capable of strategical, tactical and operational planning and decision making. They have a list of destinations they try to reach, and choose a path to get there using their knowledge of the network. They accelerate, brake, change ways depending on their surroundings and personality. They choose alternative solutions if trapped in traffic jams of when facing a road networks altered from their initial knowledge. In this follow-up article we would like to discuss the data and its analysis we used to calibrate and validate simulations built with MOSAIIC to study theoretical all-car evacuation of the city of Rouen. Furthermore, since MOSAIIC, we started a new project, ESCAPE (Exploring by Simulation Cities Awareness on Population Evacuation), which aims at simulating massive evacuation

Agent-based modeling of massive evacuation in a context of technological hazard. A case study of Rouen, France

En France, dans un contexte d’accident technologique, les consignes de mise en sécurité de la population préconisent le confinement à défaut de l’évacuation, pour laquelle les retours d’expérience à l’échelle d’une ville sont rares. De plus, s’il existe de nombreux documents de gestion du risque et de crise, ces derniers n’intègrent que de manière très marginale la population automobile, pour laquelle l’évacuation demeure pourtant la solution la plus adaptée. Le (bon) déroulement d’un tel processus dépend à la fois de la stratégie mise en place par les autorités publiques (le cas échéant) et des dynamiques de déplacement, rythmées par les choix opérés par chaque automobiliste. En effet, certains comportements individuels peuvent générer des conflits en quelques points du réseau routier et contribuer ainsi à une augmentation du temps nécessaire pour évacuer les automobilistes présents sur l’ensemble du réseau exposé. Ce travail de recherche s’est attaché, par la simulation multi-agents, à développer une méthode capable de rendre compte, dans l’espace et dans le temps, des conséquences que pourraient engendrer telle ou telle stratégie d’évacuation, à Rouen (Normandie). À partir d’une modélisation des déplacements quotidiens, une série de scénarios d’évacuation a été testée, combinant la mise en place ou non d’itinéraires spécifiques, le maintien ou non de la signalétique et l’adoption d’un comportement impatient de conduite par un certain nombre d’automobilistes. L’efficacité de chaque stratégie, définie en termes de durée d’évacuation totale, est complétée par une analyse cartographique et dynamique des zones problématiques (saturées) du réseau rouennais.In France, when an industrial accident occurs, the population confinement mainly prevails over its evacuation. Moreover, the latter suffers a lack of experience feedbacks, especially at the city scale. In addition, while numerous risk management and crisis documents exist, they marginally integrate the car drivers, for which evacuation does remain the most appropriate solution. The (good) progress of such a process depends both on (1) the public authorities’ strategy and (2) the choices made by each car driver during his trip. Indeed, some individual behaviors can generate conflicts in some points of the road network, and thus increase the duration of the whole network discharge. Thanks to the multi-agents simulation, we developed a method able to report the spatio-temporal consequences generated by different evacuation strategies, in Rouen (Normandy). Based on a daily travel model, a series of evacuation scenarios is tested, combining whether or not specific routes are set up, whether or not signage are maintained, and the adoption of an impatient behavior by some car drivers. The effectiveness of each strategy is defined by the total evacuation duration, and completed by a cartographic and dynamic analysis of the jammed areas of the Rouen network

MOSAIIC: City-Level Agent-Based Traffic Simulation Adapted to Emergency Situations

International audienceIn this paper, we present MOSAIIC, an agent-based model to simulate the road traffic of a city in the context of a catastrophic event. Whether natural (cyclone, earthquake, flood) or human (industrial accident) in origin, catastrophic situations modify both infrastructures (buildings, road networks) and human behaviors, which can have a huge impact on human safety. Because the heterogeneities of human behaviors, of land- uses and of network topology have a great impact on the traffic flows, the agent-based modeling is particularly adapted to this subject. In this paper, we focus on the new traffic model itself: the way geographical data is used to build a network, the various behaviors of our agents, from the individual to the collective level

Coolac Hotel card 7 side 1

The Noel Butlin Archives Centre also holds property and manager files for this hotel

Massive population evacuation in an urban context

International audienceIncreasing urban sprawl all over the world leads to an increase of vulnerabilities, as greater numbers of goods and people are exposed to hazards, both natural (flood, quakes, fires, tsunami, epidemic) and industrial (factories, plants). Population evacuation features amongst the tools political managers can use to mitigate these risks. When evacuations are decided, managers must strike a fine balance between displacing all the people needed to avoid injuries and fatalities, and not evacuating people that would finally not be struck by the hazard. Evacuated populations convoys must furthermore not lead to a sub-crisis where they become new vulnerabilities, or through disorder and density prevent the management of other vulnerabilities. There is regretfully a scarcity of tools to help risks manager make this kind of decision. We present here our works on such tools. Most risk management policies focus on a planar, continuous conception of space. Seveso Directives for example use different radius around the hazard center, a plant for example, to find which housings and business will be affected at which degree. We described in our presentation for UrbanNet 2013 how this approach was found lacking for handling road networks, both as vulnerabilities of the direct hazard, and as the means for a successful crisis management. In order to overcome this obstacle we proposed a city-wide agent based simulation called MOSAIIC to model the car traffic, both in normal and extraordinary situations. In MOSAIIC each driver is capable of strategical, tactical and operational planning and decision making. They have a list of destinations they try to reach, and choose a path to get there using their knowledge of the network. They accelerate, brake, change ways depending on their surroundings and personality. They choose alternative solutions if trapped in traffic jams of when facing a road networks altered from their initial knowledge. In this follow-up article we would like to discuss the data and its analysis we used to calibrate and validate simulations built with MOSAIIC to study theoretical all-car evacuation of the city of Rouen. Furthermore, since MOSAIIC, we started a new project, ESCAPE (Exploring by Simulation Cities Awareness on Population Evacuation), which aims at simulating massive evacuation