As dramatically increased elderly population, China is entering a society of deep aging. Due to the decline of physical functions, the elderly move slowly and have difficulty in escape. Hence, enough attention should be paid on pedestrian crowds’ evacuation in a nursing home. This paper takes Chinese old-age care institutions as the research object. Using the Massmotion based on the social force to establish the evacuation model and setting the parameters according to the movement characteristics of the elderly, this paper studied the influence of the dependent elderly on evacuation efficiency when they are distributed to the higher floors of the nursing home in different proportions. The results show that the evacuation time is significantly prolonged with the increase of the proportion of dependent elderly, and there is a controllable critical value for the proportion of dependent elderly. A speed-up phenomenon is observed when the old man enters the landing from the stairway, and meanwhile, with the increase of the proportion of dependent elderly, the acceleration position is gradually advanced, while the instantaneous speed declines. The results of this study can provide references in properly arranging the distribution of elderly accommodation and safe evacuation of the aged care institutions.

Emergency evacuation in subway fires is one of the hot issues in public safety. Based on Bayesian theory, a dynamic evacuation risk analysis model considering both psychological and behavioral responses of evacuees was proposed in this contribution. A subway fire scene was modeled using the Event Tree Analysis (ETA) according to the questionnaire survey at Nanjing Xinjiekou station. In this fire scenario, three control events (the fire alarm, the exhaust system and the evacuation route) were related to fire evacuation control and two control events (active escape and passive escape), which were specifically defined, were related to personnel characteristics. Subsequently, the probability of the final state of each scene was calculated by Monte Carlo simulation. Combined with the statistics of accidents and safe evacuation of subway fire cases from 1976 to 2013, the posterior probability distribution of safety evacuation was obtained after real-time dynamic updating of its precursor probability through Bayesian theory. Results show that the posterior probability of safety evacuation to succeed is around 0.8. This indicates that there is still a probability of 0.2 resulting in injury or fatalities in subway accidents even though most passengers are safely evacuated. It also suggests that utilization of 0.2 as the safety threshold would be an appropriate choice.