A mixed logit model for predicting exit choice during building evacuations. (October 2016)

• Record Type: Journal Article
• Authors: Lovreglio, Ruggiero; Fonzone, Achille; dell'Olio, Luigi
• Is Part Of: Transportation research. Volume 92(2016)
• Page Start: 59
• Page End: 75
• Publication Date: 2016-10
• Subjects: IBU intrinsic behavioural uncertainty -- PPBU perceptions and preferences behavioural uncertainty -- ED efficient design -- MLM mixed logit model -- MNL multinomial logit -- RP revealed preference -- RUM random utility model -- RUT random utility theory -- ST stated preference; Evacuation modelling -- Exit choice -- Social influences -- Behavioural uncertainty -- Random utility theory -- Efficient design; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2016.06.018
• Languages: English
• ISSNs: 0965-8564

Abstract

Highlights: Local exit choice during emergency is modelled using a discrete choice approach. A stated preference survey is developed using efficient design technique. Exit choice is affected by environmental factors: presence of smoke, emergency lighting and distance of exit. The presence of other evacuees and their flow though the exits affect the decision. Behavioural uncertainty is found decisive for the choice. Abstract: Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.