Kumbh Mela festival of India is one of the largest mass gathering event of huge religious importance all over the world. Large gatherings in these kind of religious events require rigorous monitoring and attention. Successful organization of such events requires synchronization among officials of different public departments such as police, health, security, communication, railways etc. The railway department plays a significant role in handling huge surge of passengers and their transportation during such events. Every 12-years Kumbh Mela is organized in the city of Prayagraj (formerly Allahabad) in northern India. The Allahabad Jn. railway station experiences huge inflow and outflow of pilgrims during Kumbh Mela. The railway authorities deploy predefined crowd movement strategies and boarding procedures for smooth transportation of pilgrims. However, these strategies are outlined based on previous experiences and ground knowledge of stakeholders. The strategies followed by railway authorities are needed to be evaluated and tested for realistic assessment and possible refinement before actual deployment. Our model is able to capture and simulate the real time behaviour of entities such as pilgrims and trains by programming them as synthetic agents. This model is helpful in analyzing the time taken by a group of pilgrims to move from a designated place to their target platform and board the train. The consumed time is calculated by simulating different movement and boarding procedures including the actual plans followed by the railway authorities. In this way it is possible to assess the efficiency of their movement plans and reasons about possible refinement.

中文翻译：

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基于Agent的建模和仿真，以估计朝圣者从阿拉哈巴德Jn到另一个地方的移动时间。Kumbh Mela-2019期间的火车站

印度的Kumbh Mela节是世界上规模最大，宗教意义重大的群众活动之一。在此类宗教活动中的大型聚会需要严格的监视和注意。此类事件的成功组织需要警察，卫生，安全，通信，铁路等不同公共部门官员之间的同步。在此类事件期间，铁路部门在处理大量旅客及其运输方面起着重要作用。Kumbh Mela每12年在印度北部的Prayagraj（前身为Allahabad）城市举办一次。阿拉哈巴德 在Kumbh Mela期间，火车站经历了大量的朝圣者流入和流出。铁路当局采用了预先定义的人群移动策略和登机程序，以使朝圣者的交通顺畅。但是，这些策略是根据以前的经验和利益相关者的基础知识来概述的。在实际部署之前，需要对铁路当局遵循的策略进行评估和测试，以进行实际评估和可能的完善。通过将模型编程为合成代理，我们的模型能够捕获和模拟诸如朝圣者和火车等实体的实时行为。该模型有助于分析一群朝圣者从指定地点转移到目标平台并登上火车所花费的时间。通过模拟不同的移动和登机程序（包括铁路当局遵循的实际计划）来计算消耗的时间。这样，可以评估其运动计划的效率以及可能进行改进的原因。这些策略是根据以往的经验和利益相关者的基础知识来概述的。在实际部署之前，需要对铁路当局遵循的策略进行评估和测试，以进行实际评估和可能的完善。通过将模型编程为合成代理，我们的模型能够捕获和模拟诸如朝圣者和火车等实体的实时行为。该模型有助于分析一群朝圣者从指定地点转移到目标平台并登上火车所花费的时间。通过模拟不同的移动和登机程序（包括铁路当局遵循的实际计划）来计算消耗的时间。这样，可以评估其运动计划的效率以及可能进行改进的原因。这些策略是根据以往的经验和利益相关者的基础知识来概述的。在实际部署之前，需要对铁路当局遵循的策略进行评估和测试，以进行实际评估和可能的完善。通过将模型编程为合成代理，我们的模型能够捕获和模拟诸如朝圣者和火车等实体的实时行为。该模型有助于分析一群朝圣者从指定地点转移到目标平台并登上火车所花费的时间。通过模拟不同的移动和登机程序（包括铁路当局遵循的实际计划）来计算消耗的时间。这样，可以评估其运动计划的效率以及可能进行改进的原因。