The Social Force Model
In the Social Force Model (SFM) of Prof. Dirk Helbing, pedestrian are considered like circles with a radius of their shoulder width. A driving force is assigned to define the motivation of agents to move towards the destination with a desired speed. Social forces make agents interact with each other and obstacles that are within their interaction range along their path to the destination with identical priority. It is considered that each obstacle has a repulsive potential field around it and the strength is inversely proportional to the distance from it. The physical interaction forces act on pedestrians only in case of physical contact such as panic situations or high density conditions or when they cannot pass each other quickly when touching because of friction. Pedestrians occasionally start walking towards attractions (shops, exhibitions) and over time they continue to move towards the desired destination again which is captured with an attractive interaction force. Also, the tendency of humans to walk in groups is included with a joining force. Human behaviour varies from one to another. Therefore, a random fluctuation is added to the sum of the exerted forces to present velocity fluctuation due to diverse behaviours.
Qualitative Validation of SFM
The SFM for pedestrian motions has been implanted and qualitatively validated considering lane formation, freezing by heating, oscillation and faster-is-slower patterns.
Toward an Accurate Microscopic Passenger Train Evacuation Model Using MassMotion
During emergency situations in trains, rapid and safe evacuation is crucial for saving lives of passengers. Computer models such as EvacTrain, STEPS, Pathfinder and FDS+Evac offer insights into potential difficulties and possible solutions to evacuation challenges in a short time and at low cost.
The application of MassMotion (a commercial available evacuation software commonly used for evacuation planning in buildings) has been investigated for passenger train evacuation using real data & a hypothetical case study under various conditions.
In the validation test, actual occupant egress rates from a fire drill conducted by the Spanish Railroad Administration in a passenger train are used to measure the reliability of MassMotion for producing accurate egress time predictions.
Further, the MassMotion passenger train simulation model is verified and compared to other existing microscopic passenger train evacuation models for a hypothetical case study. The comparison shows that microscopic models with continuous-space representation predict passenger evacuation times more accurately than discrete networks. Also, the force-based model MassMotion provides consistent and reliable egress time predictions.