Gregor Lämmel

Large Scale Microscopic Evacuation Simulation

The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as evacuation of Houston in the case of Hurricane Rita or the evacuation of coastal cities in the case of Tsunamis. A robust and flexible simulation framework for such large-scale disasters helps to predict the evacuation process. Existing methods are either geared towards smaller problems (e.g. Cellular Automata techniques or methods based on differential equations) or are not microscopic (e.g. methods based on dynamic traffic assignment). This paper presents a technique that is both microscopic and capable to process large problems.

Emergency Preparedness in the Case of a Tsunami—Evacuation Analysis and Traffic Optimization for the Indonesian City of Padang

The “Last-Mile Evacuation” research project develops a numerical last mile tsunami early warning and evacuation information system on the basis of detailed earth observation data and techniques as well as unsteady, hydraulic numerical modeling of small-scale flooding and inundation dynamics of the tsunami including evacuation simulations in the urban coastal hinterland for the city of Padang, West Sumatra, Indonesia. It is well documented that Sumatra’s third largest city with almost one million inhabitants is located directly on the coast and partially sited beneath the sea level, and thus, is located in a zone of extreme risk due to severe earthquakes and potential triggered tsunamis. “Last-Mile” takes the inundation dynamics into account and additionally assesses the physical-technical susceptibility and the socio-economic vulnerability of the population with the objective to mitigate human and material losses due to possible tsunamis. By means of discrete multi-agent techniques risk-based, time- and site-dependent forecasts of the evacuation behavior of the population and the flow of traffic in large parts of the road system in the urban coastal strip are simulated and concurrently linked with the other components.

Risk reduction at the “ Last - Mile ”: an attempt to turn science into action by the example of Padang, Indonesia

More than ever before, the last decade revealed the immense vulnerability of the world’s cities to natural hazards. Neither the tsunami in the Indian Ocean in 2004, the hurricane Katrina in 2005, the cyclone Nargis in 2008 nor the earthquakes in Sichuan in 2008 or in Haiti 2010 found the people, the city administrations or the national or international organizations well prepared in the advent of anticipated but to a large extent disregarded natural disasters. It is evident that the lack of tailor-made disaster management plans and standard operational procedures are often the crucial point in proper risk reduction approaches. This study presents an approach to transfer knowledge of an extensive multidisciplinary scientific study on risk identification into recommendations for risk reduction strategies. The study has been conducted by means of a combination of experts from different scientific communities coming from civil and coastal engineering, remote sensing, social sciences, evacuation modelling and capacity development. The paper presents the results of this research approach and interweaves key findings with recent experiences from an eyewitness on a previous hazard event. Thus, necessary tsunami hazard and vulnerability information as well as valuable insights into preparedness activities have been derived for initiating updated infrastructural designs and practical recommendations for emergency management as well as strategic spatial planning activities at the local scale. The approach was applied in the context of tsunami early warning and evacuation planning in the coastal city of Padang, Western Sumatra, Republic of Indonesia.

The MATSim Network Flow Model for Traffic Simulation Adapted to Large-Scale Emergency Egress and an Application to the Evacuation of the Indonesian City of Padang in Case of a Tsunami Warning

BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIEN

Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton-Based Approach

This article presents a new simulation approach for multidestination pedestrian crowds in complex environments. The work covers two major topics. In the first part, a novel cellular automaton CA model is proposed. The model describes the pedestrian movement by a set of simple rules and produces fundamental diagrams similar to those derived from laboratory experiments. The second topic of this work describes how the CA can be integrated into an iterative learning cycle where the individual pedestrian can adapt travel plans based on experiences from previous iterations. Depending on the setup, the overall travel behavior moves either toward a Nash equilibrium or the system optimum. The functional interaction of the CA with the iterative learning approach is demonstrated on a set of transport paradoxes. Furthermore, time series of speed and density observed in a small-scale experiment show a general agreement between the CA simulation and laboratory experiments. The scalability of the proposed approach is demonstrated on a large-scale scenario.

Towards system optimum: finding optimal routing strategies in time-dependent networks for large-scale evacuation problems

Evacuation planning crucially depends on good routing strategies. This article compares two different routing strategies in a multi-agent simulation of a large real-world evacuation scenario. The first approach approximates a Nash equilibrium, where every evacuee adopts an individually optimal routing strategy regardless of what this solution imposes on others. The second approach approximately minimizes the total travel time in the system, which requires to enforce cooperative behavior of the evacuees. Both approaches are analyzed in terms of the global evacuation dynamics and on a detailed geographic level.

Multi-scale Simulation for Crowd Management: A Case Study in an Urban Scenario

Safety, security, and comfort of pedestrian crowds during large gatherings are heavily influenced by the layout of the underlying environment. This work presents a systematic agent-based simulation approach to appraise and optimize the layout of a pedestrian environment in order to maximize safety, security, and comfort. The performance of the approach is demonstrated based on annual “Salone del mobile” (Design Week) exhibition in Milan, Italy. Given the large size of the scenario, and the proportionally high number of simultaneously present pedestrians, the computational costs of a pure microscopic simulation approach would make this hardly applicable, whereas a multi-scale approach, combining simulation models of different granularity, provides a reasonable trade off between a detailed management of individual pedestrians and possibility to effectively carry out what-if analyses with different environmental configurations. The paper will introduce the scenario, the base model and the alternatives discussing the achieved results.

Getting Out of the Way: Collision-Avoiding Pedestrian Models Compared to the RealWorld

Numerical simulation of human crowds is a challenging task and a number of models to simulate pedestrian dynamics on a microscopic level have been established. One aim of those models is to reproduce a realistic, and in particular collision-free, movement of crowds in complex environments. This work investigates three approaches on their capability to reproduce a collision-free movement of pedestrian crowds in complex dynamic environments. The baseline model is the well-known social force model. While in the social force model pedestrians do not explicitly avoid each other, the second model extends the social force model to avoid collisions explicitly. The observed collision-avoiding behavior produced by the third model is reached by calculating velocity obstacles. These are obstacles in the velocity space, meaning that if a pedestrian chooses a velocity that lies inside the velocity obstacle, then a collision occur at some time. This work discusses the models and their integration in a multi-agent simulation framework. The models are tested on data from a real-world experiment conducted at Technische Universitat Berlin. In this experiment, two pedestrian flows intersected at an angle of 90∘. The models’ performance with regard to the reproduction of a realistic crowds movement and their computational complexity are discussed in this work.

Risk Minimizing Evacuation Strategies under Uncertainty

This paper presents results on the simulation of the evacuation of the city of Padang with approximately 1,000,000 inhabitants. The model used is MATSim (www.matsim.org). Three different strategies were applied: shortest path solution, user optimum, system optimum, together with a constraint that moves should reduce risk whenever possible. The introduction of the risk minimization increases the overall required safe egress time (RSET). The differences between the RSET for the three risk minimizing strategies are small. Further quantities used for the assessment of the evacuation are the formation of congestion and the individual RSETs (in comparison with the available SET).

A CA model for bidirectional pedestrian streams

The modeling of pedestrian flows is of particular importance for the planning of pedestrian facilities and the preparation for emergency situations. Even though there is a wide variety of simulation models on the market, a simulation model that deals with bidirectional pedestrian flow adequately is still missing. This contribution proposes an event-based cellular automaton model that is capable of simulating bi- and unidirectional pedestrian streams. The model is built on a theoretically sound foundation. Its performance is demonstrated by a comparison to empirical data.