گنجاندن اثرات زیست محیطی در مدل سازی رفتار سیستم فرمان با استفاده از منطق فازی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|46366||2014||14 صفحه PDF||سفارش دهید||8470 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 41, Issue 4, Part 2, March 2014, Pages 1901–1914
This paper investigates the effectiveness of a fuzzy logic-based approach to modelling of pedestrian steering behaviours through built environments under normal, non-panic conditions. The proposed approach considers the effects of surrounding objects on a pedestrian’s walking path. The developed model associates vague and fuzzy characteristics of a pedestrian’s environmental perceptions with his/her steering behaviours. This is a challenging problem, as a pedestrian’s perceptions in a specific environment vary from one individual to another, and are subjective in nature. To formulate a realistic model with a high degree of fidelity, a number of factors that include variable pedestrian speeds and step-lengths are incorporated. To validate the proposed fuzzy logic model, a hallway in an indoor environment is used as a case study. A dynamic contour map that represents the effects of physical perceptible objects within the pedestrian’s field of view is established, and the proposed model is deployed to yield the predicted walking path of a pedestrian through a corridor. The environmental stimuli are modelled as attractive or repulsive socio-psychological forces that affect the pedestrian’s decision in choosing the next step position of the walking trajectory. A data set containing real walking trajectories is collected using appropriate motion tracking devices for evaluation of the proposed model. Four different scenarios are used for evaluation. The predicted walking paths from the fuzzy logic model and the real ones (collected from real experiments) are analysed and compared. The results in terms of statistical error measurements show improved performance in the scenario with variable speeds and step-lengths. The outcomes positively demonstrate the usefulness of the proposed approach in modelling pedestrian steering behaviours.