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

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. This paper describes a complex evacuation simulation framework for the city of Pandang, with approximately 1,000,000 inhabitants. Padang faces a high risk of being inundated by a tsunami wave. The evacuation simulation is based on the MATSim framework for large-scale transport simulations. Different optimization parameters like evacuation distance, evacuation time, or the variation of the advance warning time are investigated. The results are given as overall evacuation times, evacuation curves, an detailed GIS analysis of the evacuation directions. All these results are discussed with regard to their usability for evacuation recommendations.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie

Path Finding and Collision Avoidance in Crowd Simulation

Motion planning for multiple entities or a crowd is a challenging problem in today’s virtual environments. We describe in this paper a system designed to simulate pedestrian behaviour in crowds in real time, concentrating particularity on collision avoidance. On-line planning is also referred as the navigation problem. Additional difficulties in approaching navigation problem are that some environments are dynamic. In our model we adopted a popular methodology in computer games, namely A* algorithm. The idea behind A* is to look for the shortest possible routes to the destination not through exploring exhaustively all the possible combination but utilizing all the possible directions at any given point. The environment is formed in regions and the algorithm is used to find a path only in visual region. In order to deal with collision avoidance, priority rules are given to some entities as well as some social behaviour

VELOS : a VR platform for ship-evacuation analysis

Virtual Environment for Life On Ships (VELOS) is a multi-user Virtual Reality (VR) system that aims to support designers to assess (early in the design process) passenger and crew activities on a ship for both normal and hectic conditions of operations and to improve ship design accordingly. This article focuses on presenting the novel features of VELOS related to both its VR and evacuation-specific functionalities. These features include: (i) capability of multiple users’ immersion and active participation in the evacuation process, (ii) real-time interactivity and capability for making on-the-fly alterations of environment events and crowd-behavior parameters, (iii) capability of agents and avatars to move continuously on decks, (iv) integrated framework for both the simplified and advanced method of analysis according to the IMO/MSC 1033 Circular, (v) enrichment of the ship geometrical model with a topological model suitable for evacuation analysis, (vi) efficient interfaces for the dynamic specification and handling of the required heterogeneous input data, and (vii) post-processing of the calculated agent trajectories for extracting useful information for the evacuation process. VELOS evacuation functionality is illustrated using three evacuation test cases for a ro–ro passenger ship

Data Assimilation for Agent-Based Simulation of Smart Environment

Agent-based simulation of smart environment finds its application in studying people’s movement to help the design of a variety of applications such as energy utilization, HAVC control and egress strategy in emergency situation. Traditionally, agent-based simulation is not dynamic data driven, they run offline and do not assimilate real sensor data about the environment. As more and more buildings are equipped with various sensors, it is possible to utilize real time sensor data to inform the simulation. To incorporate the real sensor data into the simulation, we introduce the method of data assimilation. The goal of data assimilation is to provide inference about system state based on the incomplete, ambiguous and uncertain sensor data using a computer model. A typical data assimilation framework consists of a computer model, a series of sensors and a melding scheme. The purpose of this dissertation is to develop a data assimilation framework for agent-based simulation of smart environment. With the developed data assimilation framework, we demonstrate an application of building occupancy estimation which focuses on position estimation using the framework. We build an agent based model to simulate the occupants’ movement s in the building and use this model in the data assimilation framework. The melding scheme we use to incorporate sensor data into the built model is particle filter algorithm. It is a set of statistical method aiming at compute the posterior distribution of the underlying system using a set of samples. It has the benefit that it does not have any assumption about the target distribution and does not require the target system to be written in analytic form .To overcome the high dimensional state space problem as the number of agents increases, we develop a new resampling method named as the component set resampling and evaluate its effectiveness in data assimilation. We also developed a graph-based model for simulating building occupancy. The developed model will be used for carrying out building occupancy estimation with extremely large number of agents in the future

Human movement and behaviour simulation using gaming software

The provision of urban transportation systems that are inclusive and allow full participation in society for older people and people with disabilities is an important aspect of urban sustainability. This includes improving the design of transportation interchanges where divers individual humans interact in a crowded area. Simulation is an example of a beneficial method that can be widely applied to visualise and understand the problems using virtual environments. This research focuses on the development of simulation tools to simulate human movement and behaviour in crowded areas. A video observational method was applied as an input to understand and analyse human movement and behaviour in the real world. Six hours of video recording were recorded at a multi-mode transportation system covering weekdays, weekend, peak and off-peak times. Almost 19,000 individual humans were observed and the behaviour that they exhibited can be divided into six different types (known as Moving Through, Move-Stop-Move, Queuing, Competitive, Avoiding and Passing Through) which were determined from three major human movement types of free, same and opposite direction. Object-oriented gaming software was used to simulate the human movement and behaviour in the virtual environment based on agent-based modelling. Six factors affecting human movement and behaviour in the real world including Personal Objective, Visual Perception, Speed of Movement, Personal Space, Crowd Density and Avoidance Angle or Distance were considered as the parameters for the virtual humans. Case studies considering free, same and opposite direction movement with multi-mode transportation systems, bottleneck and non-bottleneck situations were applied to validate the prototype software system

Comparison of crowd simulation for building evacuation and an alternative approach

This paper presents an overview of crowd simulation models, their limitations, and an alternative agent-based approch. First we introduce several methods and then we focus on two widely used and validated simulation tools that use grid-based models. We discus the artifacts that these models introduce regarding the way they treat the space and the implication that this has in the movement of the agents during the simulation. We also describe the limitations that current commercial software tools have in terms of simulating human psychology and physiology. The paper discusses an agent-based alternative approach developed to overcome these limitations. The model allows for the simulation of human movement that can provide results more closely describing behavior of real people during an emergency situation. Flow rates, densities and speeds emerge in our model from the physical interactions between people instead of being predefined.Postprint (published version