This paper presents a model of pedestrian behavior to simulate and understand the mechanisms of panic and jamming in crowd situations. The authors propose a model based on socio-psychological and physical forces influencing pedestrian movement. The model incorporates both individual and collective behaviors, and accounts for factors such as desired velocity, acceleration time, and interaction forces between pedestrians and walls. The model is used to simulate various phenomena observed in escape panics, including clogging, the "faster-is-slower effect," and mass behavior. The model shows that when desired velocities are high, pedestrians may experience irregular outflows due to clogging, leading to delays and increased risk of injury. The "faster-is-slower effect" occurs when increased desired velocity leads to reduced average speed due to friction effects. The model also demonstrates that mass behavior, such as following others, can lead to inefficient use of exits and increased risk of jamming. The authors suggest that the optimal escape strategy is a balance between individualistic and herding behavior. This is supported by the model's ability to reproduce observed phenomena, including pressure buildup, clogging effects, and inefficient use of alternative exits. The model can be used to test buildings for their suitability in emergency situations and to estimate casualties. The study highlights the importance of avoiding bottlenecks in the design of public spaces and the need for wider exits to prevent jamming. It also emphasizes the role of individual variation in pedestrian behavior and the need for further research to improve the model and test it against real-world data. The authors call for complementary data and additional video material to refine the model and compare it with alternative theories.This paper presents a model of pedestrian behavior to simulate and understand the mechanisms of panic and jamming in crowd situations. The authors propose a model based on socio-psychological and physical forces influencing pedestrian movement. The model incorporates both individual and collective behaviors, and accounts for factors such as desired velocity, acceleration time, and interaction forces between pedestrians and walls. The model is used to simulate various phenomena observed in escape panics, including clogging, the "faster-is-slower effect," and mass behavior. The model shows that when desired velocities are high, pedestrians may experience irregular outflows due to clogging, leading to delays and increased risk of injury. The "faster-is-slower effect" occurs when increased desired velocity leads to reduced average speed due to friction effects. The model also demonstrates that mass behavior, such as following others, can lead to inefficient use of exits and increased risk of jamming. The authors suggest that the optimal escape strategy is a balance between individualistic and herding behavior. This is supported by the model's ability to reproduce observed phenomena, including pressure buildup, clogging effects, and inefficient use of alternative exits. The model can be used to test buildings for their suitability in emergency situations and to estimate casualties. The study highlights the importance of avoiding bottlenecks in the design of public spaces and the need for wider exits to prevent jamming. It also emphasizes the role of individual variation in pedestrian behavior and the need for further research to improve the model and test it against real-world data. The authors call for complementary data and additional video material to refine the model and compare it with alternative theories.