Abstract
Pedestrian evacuation dynamics in a classroom is always a complex process influenced by many fuzzy factors. It is very difficult and inappropriate to quantify the impact of these fuzzy factors by using the mathematical formula. Existing microscopic simulation models have made many efforts to use accurate mathematical method to model the fuzzy interaction behaviors between pedestrians under the view-limited condition. This study tries to fill this gap by establishing a microscopic simulation model which can represent the fuzzy behaviors of pedestrians under view-limited condition. The developed fuzzy social force model (FSFM) combines fuzzy logic into conventional social force model (SFM). Different from existing models and applications, FSFM adopts fuzzy sets and membership functions to describe the pedestrian evacuation process. Seven fuzzy sets are defined for this process, such as stop/go, moving direction, desired force, force from obstacles, force from pedestrian, force from indicators, and acceleration. Membership function of each input factor is calibrated based on the observed data. Model performance is verified by comparing speed distribution, velocity-density relationship, and results of simulation and observation evacuation time. Besides, the proposed model is applied to assess the number and space distribution of exit indicators and stickers. By comparing simulation results with existing models, the paper concludes that FSFM is able to well reproduce pedestrian movement dynamics in real world under view-limited condition.
Highlights
Pedestrian microscopic simulation model is a convenient and effective tool to evaluate the effectiveness of new facilities or designs
The idea of social force model is used to calculate the acceleration of pedestrian at every simulation step. is paper establishes a model based on the fuzzy logic model and social force model to solve the pedestrian dynamic evacuation problem under view-limited condition
Moving direction of each pedestrian is modeled by three subsets, such as exit, indicator, and random behavior. All these input and output factors adopt linguistic terms to explain, because this paper focuses on developing a fuzzy social force model (FSFM) method innovatively, so a relatively simple simulation scene is assumed to reduce the difficulty of model building
Summary
Pedestrian microscopic simulation model is a convenient and effective tool to evaluate the effectiveness of new facilities or designs. Based on the idea of fuzzy logic and cellular automata, Liu et al [15] developed a CA model to simulate the pedestrian dynamic evacuation in the room where they have several exits. E above research studies focus on modifying the shortcomings of the initial social force model by adding other forces As these models basically simulate the fuzzy cognitions, so calibration is very challenging. Is paper establishes a model based on the fuzzy logic model and social force model to solve the pedestrian dynamic evacuation problem under view-limited condition. Ese linguistic rules are able to be adopted to model pedestrian decision-making process, such as stop/go behavior, following willing, and walking according to indicators In this way, the pedestrian fuzzy behaviors under view-limited condition can be modeled in a very clear and straightforward way. Where f oα (t) and f oα (t) are the sociopsychological and sppheycstiicvaellyf;o→nr→coeαs(tb)eitswtheeenvepcetodresptoriianntinαg obstacle o; t oα(t) is vertical vector of and obstacle o, f→nroomα(pt)e.destrian reα to
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