ABSTRACT
Crowd motion simulation requires specification of a range of parameters, each reflecting certain aspects of agent behavior. But what parameters matter the most? Are they all equally important? The question is important given that available data and resources for parameter calibration are limited, and priorities often need to be made. Here, for the first time, a full-spectrum sensitivity analysis of crowd model parameters is reported. It is shown that estimates of simulated evacuation time are, by far, most dependent on the value of locomotion/operational parameters, especially those that determine discharge rate at bottlenecks. The next most critical set of parameters are those that influence change of direction choices. If a crowd simulation model fails to reproduce bottleneck flows accurately, efforts to refine other modeling layers will be in vain. Similarly, if the model fails to represent exit choice adaptation/changing accurately, efforts to refine the exit choice model will be fruitless.
Acknowledgments
Milad Haghani acknowledges the funding contribution that he received from the Australian Research Council, Grant No. DE210100440.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplemental data
Supplemental data for this article can be accessed online at https://doi.org/10.1080/19427867.2023.2195729
Notes
1. The experiments were conducted for the ultimate purpose of developing/calibrating various layers of this crowd simulation model, although from each experiment, secondary findings and observations might have been obtained. But each experiment was mainly tailored to calibrating a specific modeling layer and its design was customized for that purpose.
2. Prior to choosing this number, extensive testings were conducted to determine how many repetitions leads to convergence of average evacuation time. In most cases, 30 repetition was practically enough. But conservatively, each simulation has been repeated 100 times for the purpose of this study and averages are taken over that many number of repetitions.
3. This particularly important given that in areas of high densities, our empirical knowledge is limited.