An agent-based social forces model for driver evacuation behaviours

Abstract

Realistic modelling of driver behaviour during evacuation scenarios is vitally important for creating effective training environments for disaster management. However, few current models have satisfactorily incorporated the level of complexity required to model the unusual driver behaviours which occur in evacuations. In particular, few state-of-the-art traffic simulators consider desires of a driver other than to travel the quickest route between two points. Whereas in real disaster settings, empirical evidence suggests other key desires such as that of being near to other vehicles. To address this shortcoming, we present an agentbased behaviour model based on the social forces model of crowds, which explicitly includes these additional factors. We demonstrate, by using a metric of route similarity, that our model is able to reproduce the real-life evacuation behaviour whereby drivers follow the routes taken by others. The model is compared to the two most commonly used route choice algorithms, that of quickest route and real-time re-routing, on three road networks: an artificial "ladder" network, and those of Louisiana, USA and Southampton, UK. When our route choice forces model is used our measure of route similarity increases by 21-169 %. Furthermore, a qualitative comparison demonstrates that the model can reproduce patterns of behaviour observed in the 2005 evacuation of the New Orleans area during Hurricane Katrina.

The Impact of Traffic Incident Locations on a Metropolitan Evacuation

“…In the area modeled, there were limited high -capacity routes available for evacuation. Although local agencies did not plan to restrict exiting vehicle flow from the interstate, researchers assumed traffic would avoid low-capacity local roads, as suggested by [33]. The primary focus of convergence was arterial route Illinois 15 from the city of East St. Louis to Interstate 255.…”

Integrating spatial accessibility in the design of volcano evacuation plans in the French West Indies (Guadeloupe and Martinique)

“…Our methods must be consolidated by a comparison with future work as well as an empirical validation during future volcanic crises by means of postcrisis feedback and the return on operating experience (REX). The scientific improvements of these indices will take into consideration population mobility and its integration in seasonal exposure maps (Wood and Soulard 2009;Pagneux 2015b), road interruption risk indices that integrate models of lahars propagation, the definition of evacuation itineraries that couple modelling and potential behaviours resulting from sociological field investigations, multi-agent evacuation models simulating travel times and possible congestion of the network (Lämmel et al 2010;Handford and Rogers 2012;Sahal et al 2013).…”

A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

“…It can model the dynamic changes of hazardous environments, as well as the behaviour of people in response to a disaster [67], so that the simulation outcomes can improve the understanding of evacuation processes and optimise evacuation plans [57]. For a more realistic model, spatial data can be integrated in the model at various scales [110] ranging from small areas (e.g., [65,[81][82][83][84]) to large areas (e.g., [63,68,90,91]), depending on the type of hazard being modelled. For example, fire may only impact a building, while an earthquake or tsunami can destroy a city or region.…”

“…A macroscopic model is unable to capture the level of variability of population behaviour that can be achieved through a microscopic model [58], whereas a mesoscopic model compromises both micro and macro outputs [57]. Evacuation modelling uses varying methods such as GIS [59][60][61][62], ABM [63][64][65][66][67][68], numerical models [58,69,70], cellular automata [71], linear programming [72], game theory [73] and logit models [74,75]. Of these studies, only a few are concerned with volcanic evacuation, such as Marrero et al [59,60], but, in these, the behaviour of both volcanoes and population is inadequately considered in the models (macroscopic).…”