A novel causal inference method of exit choice behaviour analysis for passenger ships during emergency evacuation

Due to the complex internal layout of passenger ships, the large number of passengers, and the presence of designated assembly points, route selection during evacuation onboard ships has increasingly become a crucial factor affecting the overall evacuation process. However, variations in passengers’ risk perception and the heterogeneity of passenger groups often lead to marked differences in exit choice behaviour. To clarify the relationship between passengers’ exit choice behaviour and influencing factors, the Double Machine Learning (DML) method is employed in this study with optimisation of the nuisance function applied to identify key factors affecting exit choice from a causal inference perspective.…

• RS
  Royal Society
• NN
  National Natural Science Foundation of China
• HE
  H2020 European Research Council