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Virtual geographic environments (VGEs) are extensively used to explore the relationship between humans and environments. Crowd simulation provides a method for VGEs to represent crowd behaviors that are observed in the real world. The social force model (SFM) can simulate interactions among individuals, but it has not sufficiently accounted for inter-group and intra-group behaviors which are important components of crowd dynamics. We present the social group force model (SGFM), based on an extended SFM, to simulate group behaviors in VGEs with focuses on the avoiding behaviors among different social groups and the coordinate behaviors among subgroups that belong to one social group. In our model, psychological repulsions between social groups make them avoid with the whole group and group members can stick together as much as possible; while social groups are separated into several subgroups, the rear subgroups try to catch up and keep the whole group cohesive. We compare the simulation results of the SGFM with the extended SFM and the phenomena in videos. Then we discuss the function of Virtual Reality (VR) in crowd simulation visualization. The results indicate that the SGFM can enhance social group behaviors in crowd dynamics. [ABSTRACT FROM AUTHOR]

The risks of group trampling during escalator transfers were studied in this paper. A state shifting model was proposed to describe the behaviors of a pedestrian during a group trampling accident. Based on the model, a group trample during escalator transfers was simulated from the beginning of the accident to the transfer recovery using the social force model. The impacts of 6 key factors were studied including the initial location of the accident, the time taken to invoke emergency measures, pedestrian velocity, escalator velocity, time taken for a fallen pedestrian to stand up, and pedestrian traffic. The results show that (1) when an accident happens in the transfer aisle, the peak number of pinned pedestrians is higher, while when it occurs near an escalator exit, the pressure exerted on the pinned pedestrians is more serious; (2) the speed of propagation of the accident is always faster than the recovery rate, and the earlier the emergency measures are taken, the less serious the accident is; (3) overall, except for the initial location of a trampling accident, which cannot be controlled, the other five factors have positive correlations with the severity of a group trampling accident, and can be descending ordered by their impacts using a regression analysis: early measures, pedestrian traffic, short standing-up delay, pedestrian velocity, and escalator velocity. These results can be referenced in the development of countermeasures to reduce group trampling risks. [ABSTRACT FROM AUTHOR]

The congestion risk during escalator transfers was simulated based on a modified social force model. A four-stage transfer model was proposed. A projection strategy was employed to calculate the social forces for inclined surfaces, and a schedule-line model was proposed to calculate the targets adaptively. Realistic simulations of escalator transfer activities were achieved. The results demonstrate that the spatial distribution of the congestion risks is inhomogeneous. A few areas contain clearly higher risks, and the congestion risk is higher in the transfer aisles than on the escalators. The congestion risk in the transfer aisle is influenced more by the average pedestrian speed than that of the escalators. Slower walkers in the transfer aisle may cause congestion, which is more serious when the escalator speed is faster than that of the pedestrians. Therefore, to reduce the congestion risk, the speed of the escalator should be set slower than the average speed of the pedestrians, and conductors can be employed to divert the traffic at the entrance, turns, and exit of the escalator. [ABSTRACT FROM AUTHOR]

Abstract: A type of trampling process that is caused by picking-up activities during escalator transfers was studied in this paper. A five-stage trampling model for individual pedestrians was proposed, and the social force model was modified considering the transfer features. Several scenarios were simulated to study the impacts of 4 factors, namely, pedestrian traffic, escalator velocity, picking-up duration and pedestrian velocity, on trampling probability. The results show that pedestrian traffic strongly affects the trampling probability, with a positive correlation throughout all scenarios; the picking-up duration affects the trampling probability, with a negative correlation throughout all scenarios; lower pedestrian velocities can result in higher trampling probabilities if the picking-up duration is short; and the escalator velocity may also affect the trampling probability, but there are no general rules for all scenarios. Thus, the impacts of these 4 factors can be queued in descending order as follows: pedestrian traffic picking-up duration pedestrian velocity escalator velocity. Countermeasures can be employed according to the results to reduce trampling risks. [Copyright &y& Elsevier]

To overcome the difficulties of quantitatively optimizing and evaluating evacuation guidance systems, we proposed a perception model based on virtual reality (VR) experiments and the social force model (SFM). We used VR and eye tracking devices to carry out experiments. The VR experiment data was mainly used for three purposes: to determine the parameter values of the perception model, to optimize the evacuation guidance system by quantitative analysis, and to validate the perception model. Additionally, we compared the VR experimental and model simulation results before and after the optimization to quantitatively assess the improvement in the optimized evacuation guidance system. The results showed that our model can effectively simulate the perception behaviors of evacuees on the evacuation guidance system and it can quantitatively evaluate different evacuation guidance system schemes. The model simulations showed that the optimized evacuation guidance system improved the evacuation efficiency, with the average escape time and distance of the two starting positions reduced by 37% and 28%, respectively. [ABSTRACT FROM AUTHOR]

In emergency evacuations, not all pedestrians know the destination or the routes to the destination, especially when the route is complex. Many pedestrians follow a leader or leaders during an evacuation. A Trace Model was proposed to simulate such tracing processes, including (1) a Dynamic Douglas–Peucker algorithm to extract global key nodes from dynamically partial routes, (2) a key node complementation rule to address the issue in which the Dynamic Douglas–Peucker algorithm does not work for an extended time when the route is straight and long, and (3) a modification to a follower’s impatience factor, which is associated with the distance from the leader. The tracing process of pupils following their teachers in a primary school during an evacuation was simulated. The virtual process was shown to be reasonable both in the indoor classroom and on the outdoor campus along complex routes. The statistical data obtained in the simulation were also studied. The results show that the Trace Model can extract relatively global key nodes from dynamically partial routes that are very similar to the results obtained by the classical Douglas–Peucker algorithm based on whole routes, and the data redundancy is effectively reduced. The results also show that the Trace Model is adaptive to the motions between followers and leaders, which demonstrates that the Trace Model is applicable for the tracing process in complex routes and is an improvement on the classical Douglas–Peucker algorithm and the social force model. [ABSTRACT FROM AUTHOR]