|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|588933||878661||2017||16 صفحه PDF||ندارد||دانلود رایگان|
• A calculation method is proposed to measure the guidance efficacy of signage.
• Guidance demand weights are assigned to different spatial locations.
• An analytical interaction model between the pedestrian and signage is proposed.
• A general signage system location model is proposed.
The smooth and fast evacuation of a pedestrian group is dependent on guidance services provided by signage systems. This paper investigates the location method of an evacuation signage system in a public space. We proposed a calculation method to determine the guidance efficiency of signage and further present a piece-wise probability function to explain interactions between pedestrians and signage. The interaction between one pedestrian and one signage was extended to the interaction between a pedestrian crowd and a signage system. A location model of the signage system was proposed to determine the minimum number of signs necessary to meet guidance demands. The location model was based on the Cooperative Location Set Cover Problem (CLSCP) and was correspondingly solved by a proposed exponential binary heuristic search algorithm (EBHS), i.e., a combined exponential binary search method and a heuristic search algorithm for solving the Cooperative Maximum Cover Location Problem (CMCLP). Finally, the proposed model was applied to determine the location of an evacuation signage system in a hall. The parameters used in the location model were calibrated based on experimental data. The model results showed that the proposed model can suggest the optimal number and best locations of signs. A sensitivity analysis showed that the guidance capacity of the signage system can be increased by improving the attractiveness of signage and pedestrian trust and familiarity with environment. The same number of signs is suggested for evacuation scenarios wherein crowd following behavior is present.
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Journal: Safety Science - Volume 91, January 2017, Pages 132–147