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Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management

Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management
Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management
Accurate modelling of driver behaviour in evacuations is vitally important in creating realistic training environments for disaster management. However, few current models have satisfactorily incorporated the variety of factors that affect driver behaviour. In particular, the interdependence of driver behaviours is often seen in real-world evacuations, but is not represented in current state-of-the art traffic simulators. To address this shortcoming, we present an agent-based behaviour model based on the social forces model of crowds. Our model uses utility-based path trees to represent the forces which affect a driver's decisions. 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 Lousiana, USA and Southampton, UK. When our route choice forces model is used our measure of route similarity increases by 21%-93%. 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.
163-172
Handford, David
17089571-445b-4407-b847-ffa8be2e5bef
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Handford, David
17089571-445b-4407-b847-ffa8be2e5bef
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc

Handford, David and Rogers, Alex (2011) Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management. The Ninth International Conference on Practical Applications of Agents and Multi-Agent Systems, Spain. 06 - 08 Apr 2011. pp. 163-172 .

Record type: Conference or Workshop Item (Other)

Abstract

Accurate modelling of driver behaviour in evacuations is vitally important in creating realistic training environments for disaster management. However, few current models have satisfactorily incorporated the variety of factors that affect driver behaviour. In particular, the interdependence of driver behaviours is often seen in real-world evacuations, but is not represented in current state-of-the art traffic simulators. To address this shortcoming, we present an agent-based behaviour model based on the social forces model of crowds. Our model uses utility-based path trees to represent the forces which affect a driver's decisions. 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 Lousiana, USA and Southampton, UK. When our route choice forces model is used our measure of route similarity increases by 21%-93%. 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.

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Modelling_Driver_Interdependent_Behaviour_in_Agent-Based_Traffic_Simulations_for_Disaster_Management.pdf - Accepted Manuscript
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More information

Submitted date: 2011
Additional Information: Event Dates: 6-8 April 2011
Venue - Dates: The Ninth International Conference on Practical Applications of Agents and Multi-Agent Systems, Spain, 2011-04-06 - 2011-04-08
Organisations: Agents, Interactions & Complexity, EEE

Identifiers

Local EPrints ID: 271910
URI: https://eprints.soton.ac.uk/id/eprint/271910
PURE UUID: 00c7214f-5d1d-4a1b-af03-45ac042c968b

Catalogue record

Date deposited: 18 Jan 2011 00:19
Last modified: 18 Jul 2017 06:37

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Contributors

Author: David Handford
Author: Alex Rogers

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