RESEARCH ON THE EVACUATION OF PARKING PERSONNEL IN HIGH-SPEED TRAIN FIRE TUNNEL SECTION BASED ON ANT COLONY ALGORITHM

Abstract

Boisterous and chaotic events can always be implicated in fire and explosion emergencies requiring evacuation. The domino effect is a stampede that can in turn lead to fatalities or other pathophysiological conditions. Tensed environmental conditions lead to uncertainties for both the rescuers and rescues leaving the evacuees with no choice but to look for the nearest exit and navigate themselves away from potential danger. The situation is aggravated in conditions where the risk is at one of the only exit routes, causing emotional overwhelm and brain overload due to the need for brain re-engagement on the next safest exit. There is a need for research on the ways of automating the process of finding the best escape routes to avert the chances of a stampede or fatalities when such situations emanate, even without prior knowledge of the hazard. The objective of this paper is to research the evacuation of parking personnel in a high-speed train fire tunnel section based on an ant colony algorithm. We propose an optimally evaluated exit plan for every affected individual based on the ant colony algorithm. The main aspects looked into are; the dynamic explosion and fire spread, impaired movability that might be induced by the fire, and discredited information from the rescuers or other evacuees which might increase the risks and place other lives in jeopardy. Empirical tests on the proposed algorithms are preeminently conducted through various techniques and technologies. Fire and explosion hazards are replicated through the use of realistic fire and explosion dynamic simulators demonstrating how our proposed solutions rank against not only other static and dynamic alternates, but also real-life situations forestalling hazardous situations. The proposed solution can be used by both parties; rescuers and evacuees to devise strategies and communicate the safest routes for evacuation of the high-speed train tunnel personnel in the event of a fire outbreak. We logically follow three main steps in our research to ensure timely detection and safe evacuation; collecting credited information on the hazard, calculating the exit plan, and prompt communication of the plan to the affected individuals. Information is a very crucial fact in the case of hazardous situations such as fire outbreaks, it is thus a necessity to have plenty of it. The parking personnel in this situation have the option of downloading the software to their smartphones whenever they are in a train or a train tunnel. Through utilizing the available sensors, this software will be able to communicate the necessary information to a central location. A vast wealth of information can be acquired to aid in the escape plan. Notwithstanding the capability of the software, it may prove non-efficient in these cases if it must be manually powered. Automation is this key and this will be facilitated by our intervention. The main objective of acquiring the necessary information is to devise a rescue plan. Mathematical models have been proven to be valuable in cases where the tunnels are intricate with a lot of evacuees. The proposed solution will use the available information to calculate the most appropriate plan taking into account the nature of the fire hazard and potential repercussions. Finally, the plan should be communicated to the evacuees to rescue them from the potential hazard.