About Mohammed M. Alrashed Mohammed M. Alrashed M.S., Electrical and Computer Engineering robotics intelligent systems control systems RISC Mohammed M. Alrashed research interests are in Systems and Control with robotic applications and Mathematical Theory of Rational Behavior. Master Thesis Abstract The increasing occurrence of panic stampedes during mass events has motivated studying the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. The lack of understanding of panic stampedes still causes hundreds of fatalities each year, not to mention the scarce methodical studies of panic behavior capable of envisaging such crowd dynamics. Under those circumstances, there are thousands of Events Presented Events Nov 8 - Nov 14, 2020 Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management Mohammed M. Alrashed, M.S., Electrical and Computer Engineering Nov 11, 20:00 - 21:00 KAUST resource management risk assessment computational models Abstract We develop a computational framework for risk mitigation in high population density events. With an increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management, and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed
Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management Mohammed M. Alrashed, M.S., Electrical and Computer Engineering Nov 11, 20:00 - 21:00 KAUST resource management risk assessment computational models Abstract We develop a computational framework for risk mitigation in high population density events. With an increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management, and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed
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