An agent-based social forces model for driver evacuation behaviours

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 agent-based 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.