Train crashes are somehow rare to occure. They occur once in almost two years due to the management and scheduling of trains in railway stations. It is important to manage strains efficiently and competently because a single train crash can kill hundreds of train passengers. This was witnessed in April 25, 2005 in Amagasaki in Japan when a train crash occurred due to derailment killing hundreds and injuring scores others(Britton, et al, 2017). The seven carriage commuter train rammed into an apartment building where it slid into the first floor parking garage and took several days to remove. The second carriage slammed into the corner of the building and was pushed with the weight of the remaining carriages. 700 people were on board of the train at the time of the crash, 106 people were killed and 562 were injured. This was the second most deadliest train crash accident since 1963 where a derailed freight train killed 162 people. Most of the people who witnessed the crash said the train was speeding (Brod, & Leslau, 2014).
The investigators focused on the speed of the train as the most viable reason as to why the train crashed. The 23 year old driver was among the dead was seen as the reason for the derailment. It was shown that 25 minutes before the trains derailment, the 23 year old identified as Takami had run a red light which caused an automatic train stop(ATS) which had brought the train to a halt. At an earlier stop, the train had overshot the correct stopping position which required him to back up the train. This had also resulted into a one and a half minute delay just four minutes before the crash. The train was speeding at more than 120km/hr (Britton, et al, 2017). Investigators noted that the driver may have been trying to recover the lost time hence over speeding. Many reports from the surviving passengers said that the train was travelling faster than the normal speeds. The investigators also noted that he may have been stressed as he could have been punished for bypassing the red light at Itami station (Clothier & Walker,2015).
The Japanese west railway station is very strict on time keeping and punctuality and had created a good reputation amongst the passengers. 10 months earlier, he had been reprimanded for overshooting a platform by over 100 meters. Drivers would face financial penalties for lateness as well as a forced retraining programs which is not only harsh but humiliating. The humiliation included weeding and cutting grass during the day (Glendon ,et al,2016). The driver was trying to avoid such harsh conditions. The retraining program also included very harsh verbal abuse forcing the drivers to issue long reports to apologize for their mistakes. The program was also forcing the drivers to perform minor tasks such as cleaning the surrounding. Many of the drivers said that the program was psychological torture and punitive.
The drivers were also receiving non-essential phone calls from general control station at the specific time that he was approaching the bend. The train was moving at a speed of 116 km/hr instead of the recommended 70 km/hr in bended curves. The investigations revealed that the driver was stressed and would have to receive the punishment due to the two infractions he had committed (Heffner,2017).. After the investigations and several tests, the investigators noted that the train could derail in the corner if it was going at any speeds beyond 106km/h. he was too fast on that corner. Due to the psychological torture that he knew he would undergo after the infractions, he never noticed that he was actually speeding and therefore causing the derailment. When the driver noticed that he was speeding , he used the service brake instead of the emergency brake since he had to justify the second use of the emergency brake (Liu, et al,2017)..
The scale and consequences of accidents and wrecks occurring in railway transport can significantly increase when they enter into their zone of various harmful substances, called when they are transported by dangerous goods. Therefore, all accidents with them are classified separately as emergency situations with dangerous goods.
The emergency situation with dangerous goods (AS with OG) is an emergency situation under conditions different from the conditions for the normal carriage of goods related to fire, leakage, spillage of dangerous goods, damage to containers or rolling stock with dangerous cargo that may lead or lead to an explosion, fire, poisoning, radiation, disease, trauma, death of people and animals.
In turn, the AU with the OG, depending on their consequences, are divided into incidents (accidents) and accidents. Accidents include explosion and combustion of exhaust gas in the carriage or its release from a carriage or container with severe consequences, which are: death and damage to human health; carrying out the evacuation of personnel or the population; damage to the environment and pollution of water supply sources; damage to the rolling stock to the degree of de-commissioning (write-off).
Incidents (accidents) include: collisions and collisions of rolling stock with exhaust emissions; uncoupling carriages from exhaust trains from trains (with their technical or commercial malfunction, violation of the rules of transportation of the OG); the presence of carriages, containers or cargo spaces in the accident zone; ignition or leakage (spillage) of exhaust gases from a car or container without serious consequences (Li, et al,2018).
In addition to internal causes, emergency situations on the railways can also be caused by a number of external causes.
– dangerous natural phenomena, natural and other disasters;
– Major industrial accidents and catastrophes on potentially dangerous objects of the economy located near railways;
Risks and challenges
Risks, Challenges, Threats. An important methodological explanation should be made here. Risks, challenges and threats we consider as different degrees of danger. In this terminology, risks are the lowest level of danger, and threats are the highest (Underwood, & Waterson, 2014).. At the same time, the most important component of the national security policy is the mastering and skillful application of technologies for transferring threats to challenges, and challenges – to risks. If the risks turn into calls, and threats are called, then this is an obvious sign of serious disruptions in the national security system of a particular country.
Let us illustrate this situation at first with a simple domestic example. Anyone, even a very experienced driver, sitting behind the wheel of a train and driving on a rail, exposes his personal safety and the safety of his passengers to a certain risk. The train driver, exceeding the set speed, moves the danger to a higher level – the level of the call. If he sits behind the wheel in a state of disturbed mind or drives a train without paying attention to railway station signs, then this is a threat both for his personal safety and for the safety of passengers.
Conclusions
The investigations describes the organization and conduct of safety expertise at railway stations. The purpose of this study was to assess the optimality of the safe arrangement of railway stations, taking into account such characteristics as equipment cost, safety (probability of failure-free operation), operating costs, durability, installation time (Saat,et al,2014).
References
Brod, D., & Leslau, B. (2014). BNSF San Bernardino Case Study: Positive Train Control Risk Assessment (No. DOT/FRA/ORD-14/31).
Britton, M. A., Asnaashari, S., & Read, G. J. (2017). Analysis of train derailment cause and outcome in Victoria, Australia, between 2007 and 2013: Implications for regulation. Journal of Transportation Safety & Security, 9(1), 45-63.
Clothier, R. A., & Walker, R. A. (2015). Safety risk management of unmanned aircraft systems. In Handbook of unmanned aerial vehicles (pp. 2229-2275). Springer, Dordrecht.
Glendon, A. I., Clarke, S., & McKenna, E. (2016). Human safety and risk management. Crc Press.
Heffner, M. D. (2017). Informing Decision-Making for Derailments Involving Hazmat: An Analysis of Phmsa Train Accident Data. California State University, Long Beach.
Liu, X., Saat, M. R., & Barkan, C. P. (2017). Freight-train derailment rates for railroad safety and risk analysis. Accident Analysis & Prevention, 98, 1-9.
Liu, X. (2015). Statistical temporal analysis of freight train derailment rates in the United States: 2000 to 2012. Transportation Research Record: Journal of the Transportation Research Board, (2476), 119-125.
Li, W., Roscoe, G. S., Zhang, Z., Saat, M. R., & Barkan, C. P. (2018). Comparison of Loaded and Empty Unit Train Derailment Characteristics (No. 18-05260).
Saat, M. R., Werth, C. J., Schaeffer, D., Yoon, H., & Barkan, C. P. (2014). Environmental risk analysis of hazardous material rail transportation. Journal of hazardous materials, 264, 560-569.
Underwood, P., & Waterson, P. (2014). Systems thinking, the Swiss Cheese Model and accident analysis: a comparative systemic analysis of the Grayrigg train derailment using the ATSB, AcciMap and STAMP models. Accident Analysis & Prevention, 68, 75-94.
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