Agent architecture for simulating pedestrians in the built environment

The paper discusses an agent architecture for investigating visualized simulated pedestrian activity and behavior affecting pedestrian flows within the built environment. The approach will lead to a system that may serve as a decision support tool in the design process for predicting the likely impact of design parameters on pedestrian flows. UML diagrams are used to communicate about the interpretation of the agent architecture

A Markov-chain Activity-based Model for Pedestrians in Office Buildings

As the number of people working in office buildings increases, there is an urgent need to improve building services, such as lighting and temperature control, within these buildings to increase energy efficiency and well-being of occupants. A pedestrian behaviour model that simulates office occupants’ movements and locations can provide the high spatial and temporal resolution data required for the testing, evaluation, and optimization of these control systems. However, since most studies in pedestrian research focus on modelling specific actions at the operational level or target situations where movement schedules do not have to modelled, a pedestrian behaviour model that can simulate complex situations over long time periods is missing. Therefore, this paper proposes a tactical level model to generate occupant movement patterns in office buildings. The Markov-chain activity-based model proposed here is data parsimonious, flexible in accepting different levels of information, and can produce high resolution output. The mathematical properties of the methodology are analyzed to understand their impact on the final results. Finally, the tactical level pedestrian behaviour model is face validated using a case study of an imaginary office with a simple layout

Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review

Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article's contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area

An Artificial Neural Network Framework for Pedestrian Walking Behavior Modeling and Simulation

Movement behavior models of pedestrian agents form the basis of computational crowd simulations. In contemporary research, a large number of models exist. However, there is still no walking behavior model that can address the various influence factors of movement behavior holistically. Thus, we endorse the use of artificial neural networks to develop walking behavior models because machine learning methods can integrate behavioral factors efficiently, automatically, and data-driven. In this paper, we support this approach by providing a framework that describes how to include artificial neural networks into a pedestrian research context. The framework comprises 5 phases: data, replay, training, simulation, and validation. Furthermore, we describe and discuss a prototype of the framework

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network