Abstract
Coach emergency escape research is an effective measure to reduce casualties under serious vehicle fire accidents. A novel experiment method employing a wireless transducer was implemented and the head rotation speed, rotation moment and rotation duration were collected as the input variables for the classification and regression tree (CART) model. Based on this model, the classification result explicitly pointed out that the exit searching efficiency was evolving. By ignoring the last three unimportant factors from the Analytic Hierarchy Process (AHP), the ultimate Dynamic Bayesian Network (DBN) was built with the temporal part of the CART output and the time-independent part of the vehicle characteristics. Simulation showed that the most efficient exit searching period is the middle escape stage, which is 10 seconds after the emergency signal is triggered, and the escape probability clearly increases with the efficient exit searching. Furthermore, receiving emergency escape training contributes to a significant escape probability improvement of more than 10%. Compared with different failure modes, the emergency hammer layout and door reliability have a more significant influence on the escape probability improvement than aisle condition. Based on the simulation results, the escape probability will significantly drop below 0.55 if the emergency hammers, door, and aisle are all in a failure state.
Highlights
Vehicle fire hazards on coaches resulting from collision or self-ignition account for massive losses of lives and economic damage in China [1]
Passenger behaviors were different according to the individual state of mind, from which we can mine the relationship between behaviors and escape efficiency
In order to study the escape behavior in the long queue circumstances, which is common in coach accidents, we focused on the second stage mentioned before, and built a classification and regression tree (CART) model to learn and estimate the efficiency produced by different escape behaviors
Summary
Vehicle fire hazards on coaches resulting from collision or self-ignition account for massive losses of lives and economic damage in China [1]. Each of these factors is closely related to the escape method and survival rate Objective factors, such as the complexity of emergency exit handling, play an important role in emergency fire traffic accidents and draw the attention of researchers to the coach evacuation factor analysis. A spatio-temporal probability model integrating crowd and hazard dynamics was built according to different fire points and route selections on the ship In these DBN research papers, an important common ground exists that the values used in the conditional probability table can be obtained either from official data or expert suggestions. The dynamic evacuation details, like those applied to ship evacuation, still need to be developed To address this problem and estimate the result in an emergency situation, a DBN based risk assessment method for individual coach evacuation and factors of importance affecting the escape procedure were analyzed in the last part.
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