دانلود مقاله ISI انگلیسی شماره 64416
ترجمه فارسی عنوان مقاله

یک سیستم فازی ژنتیک برای مدل مسیر پیاده روی عابر پیاده در یک محیط ساخته شده

عنوان انگلیسی
A genetic fuzzy system to model pedestrian walking path in a built environment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
64416 2014 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Simulation Modelling Practice and Theory, Volume 45, June 2014, Pages 18–34

ترجمه کلمات کلیدی
پیش بینی مسیر پیاده روی ؛ مدل سازی رفتار عابرین؛ سیستم های فازی ژنتیک؛ ادراک محیطی عابر پیاده
کلمات کلیدی انگلیسی
Walking trajectory prediction; Pedestrian behaviour modelling; Genetic fuzzy system; Pedestrian environmental perception
پیش نمایش مقاله
پیش نمایش مقاله  یک سیستم فازی ژنتیک برای مدل مسیر پیاده روی عابر پیاده در یک محیط ساخته شده

چکیده انگلیسی

A study on the pedestrian’s steering behaviour through a built environment in normal circumstances is presented in this paper. The study focuses on the relationship between the environment and the pedestrian’s walking trajectory. Owing to the ambiguity and vagueness of the relationship between the pedestrians and the surrounding environment, a genetic fuzzy system is proposed for modelling and simulation of the pedestrian’s walking trajectory confronting the environmental stimuli. We apply the genetic algorithm to search for the optimum membership function parameters of the fuzzy model. The proposed system receives the pedestrian’s perceived stimuli from the environment as the inputs, and provides the angular change of direction in each step as the output. The environmental stimuli are quantified using the Helbing social force model. Attractive and repulsive forces within the environment represent various environmental stimuli that influence the pedestrian’s walking trajectory at each point of the space. To evaluate the effectiveness of the proposed model, three experiments are conducted. The first experimental results are validated against real walking trajectories of participants within a corridor. The second and third experimental results are validated against simulated walking trajectories collected from the AnyLogic® software. Analysis and statistical measurement of the results indicate that the genetic fuzzy system with optimised membership functions produces more accurate and stable prediction of heterogeneous pedestrians’ walking trajectories than those from the original fuzzy model.