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Discrete Choice Models to Determine High-speed Passenger Stop Under Emergency Conditions

机译:紧急情况下确定高速旅客停车站的离散选择模型

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High Speed railways are one of the most reliable means of transport. Security and reliability are important so the system has to be prepared to take action in case something goes wrong. It is crucial for a railway management plan to have emergency procedures for a quick response in case of incident or accident. In this paper a model is presented that locates the stop of a train in a certain area during an incident or accident using discrete choice models. This model will support future decision making protocols. Random utility theory assigns utility to each corner of the railway network to calculate where the most suitable place to stop the train is depending on variables such as train speed, place of failure, or type of accident or incident, among others. A minimum computational cost model provides results, which support decision-making procedures on high-speed trains during emergency situations. This paper presents a methodology to determine the most suitable place to safely stop a train in the minimum time and the procedure could be included in future safety standards and emergency protocols. Both external and internal data from the railway are calibrated to predict the most likely place to stop. Not only the stop is predicted but the model also considers timetable effects, meaning the methodology can also be applied to schedule-based railway systems, a characteristic that endows the method with great potential since it considers minimal impacts on schedules.
机译:高速铁路是最可靠的运输方式之一。安全性和可靠性很重要,因此必须准备好采取措施以防万一出现问题。铁路管理计划中必须有应急程序,以便在发生事故或事故时迅速做出响应,这一点至关重要。在本文中,提出了一个模型,该模型使用离散选择模型在事件或事故发生期间在特定区域定位火车的停靠站。该模型将支持将来的决策协议。随机效用理论将效用分配给铁路网络的每个角落,以计算最合适的火车停靠地点,具体取决于诸如火车速度,故障地点,事故或事件类型等变量。最小计算成本模型可提供结果,这些结果可在紧急情况下支持高速列车的决策程序。本文提出了一种方法,可以确定在最短的时间内安全停止火车的最合适地点,并且该程序可以包含在将来的安全标准和紧急情况协议中。铁路的内部和外部数据均经过校准,以预测最可能的停车地点。不仅可以预测停靠点,而且该模型还考虑了时间表的影响,这意味着该方法还可以应用于基于时间表的铁路系统,该特性由于该方法对时间表的影响最小,因此具有很大的潜力。

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