Modeling Perception And Overtaking Behavior For Crowd Dynamics Using Modified Social Force Model

dc.contributor.authorHassan, Ummi Nurmasyitah
dc.date.accessioned2022-10-06T07:16:16Z
dc.date.available2022-10-06T07:16:16Z
dc.date.issued2020-07
dc.description.abstractThe Social Force Model (SFM) is one of the most popular models to describe the motion of pedestrians as it is able to simulate the behavior of pedestrians using simple mathematical equations. Many modifications have been done to improve the SFM such as the incorporation of the self-slowing mechanism in dynamic respect factor (DRF) model. However, the simulations of the pedestrians produce unrealistic behavior because of the lack of the pedestrian’s perception. In modified dynamic respect factor (MDRF) model, the self-slowing mechanism is enhanced by granting this perception to the simulated pedestrian. Another modification is to incorporate the overtaking behavior in modified SFM I model, in which the pushing behavior is completely eliminated, and the overtaking behavior is modeled with minimal modifications to the basic SFM. However, the overtaking behavior is partially successful in this model. Therefore, we enhance the modified SFM I (named as modified SFM II) by modifying the desired direction towards an area with less interaction between pedestrians, and modeling the repulsion strength with respect to local density and relative speeds. The physical environment is in the normal unidirectional walkway. The pedestrians movement is compared using the snapshots of the video simulations at various times. Subsequently, comparisons of the pedestrian flow pattern between DRF model, MDRF model, original Helbing model, Helbing Perception model, Yuen Visual Angle model, and modified SFM I and II models are conducted.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/16243
dc.language.isoenen_US
dc.publisherUniversiti Sains Malaysiaen_US
dc.subjectCrowd Dynamicsen_US
dc.subjectSocial Force Modelen_US
dc.titleModeling Perception And Overtaking Behavior For Crowd Dynamics Using Modified Social Force Modelen_US
dc.typeThesisen_US
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