Title :
Guidance optimization of building evacuation considering psychological features in route choice
Author :
Xuesong Lu ; Luh, Peter B. ; Marsh, Kerry L. ; Gifford, Timothy ; Tucker, Andrew
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA
Abstract :
In building evacuation problems, psychological features such as route familiarity, following the guidance and herding may influence evacuees´ route choice. Based on psychological findings, a new macroscopic network-flow model that incorporates the effects of psychological features is established in this paper. These features are unified through the notion of trust, which reveals the willingness to select the route indicated by different features. The optimization problem is then formulated to reduce evacuees´ risk by optimizing crowd guidance. To efficiently solve this problem, a divide-and-conquer approach is used. The subproblem for one group may be coupled with another when the two groups merge together because of herding, and possible herding situations are separately calculated. The above model is partially validated by virtual reality trials. Pilot testing results suggest guidance is effective with psychological features in consideration.
Keywords :
behavioural sciences computing; divide and conquer methods; emergency management; optimisation; psychology; risk management; virtual reality; building evacuation guidance optimization; crowd guidance optimization; divide-and-conquer approach; evacuee risk reduction; macroscopic network-flow model; psychological features; psychological findings; route choice; route familiarity; trust notion; virtual reality; Avatars; Buildings; Fires; Layout; Optimization; Psychology; Solid modeling; Building evacuation; guidance optimization; immersive virtual reality; macroscopic model; psychological features;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053147