Human Behavioral Simulation Using Affordance-Based Agent Model

Abstract

In this paper, we propose a novel agent-based simulation modeling of human behaviors. A conceptual framework of human behavioral simulation is suggested using the ecological definition of affordances in order to mimic perception-based human actions interacting with the environment. A simulation example of a 'warehouse fire evacuation' is illustrated to demonstrate the applicability of the proposed framework. The perception-based human behaviors and planning algorithms are adapted and embedded within human agent models using the Static and Dynamic Floor Field Indicators, which represent the evacuee's prior knowledge of the floor layout and perceivable information of dynamic environmental changes, respectively. The proposed framework is expected to capture the natural manners in which humans participate in systems and enhance the simulation fidelity by incorporating cognitive intent into human behavior simulations.

Variable Message Signs for road tunnel emergency evacuations

“…It has also been used to evaluate the design of emergency exits (Sixsmith et al, 1988) and to explain the effectiveness of way-finding systems for evacuation (Nilsson, 2009). In addition, the theory has been successfully employed in fire safety research to understand individual pedestrian evacuation behaviour (Joo et al, 2013;Kim et al, 2011).…”

Towards an Affordance-Based Ad-Hoc Suitability Network for Indoor Manufacturing Transportation Processes

“…In study [35], the authors propose a methodology to generate accessibility information for impaired people. The authors of [36][37][38] elaborate on the application of affordances for path calculation and decision making of pedestrian agents. In order to model spatial suitability, the authors of [39] provide a hierarchical representation of indoor spaces considering user groups and their tasks.…”

Simulating the forest fuel market as a socio‐ecological system with spatial agent‐based methods: A case study in Carinthia, Austria

“…Any ABM can analyze a system under varying conditions, which helps to understand complex phenomena (Macal & North, 2010). In particular, agents may show different behavior ranging from goal-oriented to adaptive or autonomous one (Kim, Joo, Rothrock, Wysk, & Son, 2011). The combination of ABM and Geographical Information Systems (GIS) has been described in the literature extensively (e.g., Batty, Crooks, See, Heppenstall, 2012;Brown, Riolo, Robinson, North, & Rand, 2005;Hofmann et al, 2014;Johnston, 2013;Koch, 2008;Mandl, 2003;Raubal, 2001;Turner & Penn, 2002;Van Berkel & Verburg, 2012).…”