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Emergency modeling in transportation via queuing and game theory.

机译:通过排队和博弈论进行运输中的应急建模。

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摘要

In modern transportation network, emergencies on roadway and man-made emergencies in the infrastructure can incur enormous costs to society directly and indirectly. The direct costs include transportation cost due to incident delay and traffic congestion, and various risks brought upon the infrastructure by man-made emergencies. The indirect cost can include economic and psychological impacts on society.;Emergencies on roadways include accidents, disabled vehicles, adverse weather conditions, spilled loads, hazardous materials, etc. Under these cases, non-recurrent congestion will slow down the traffic flow on certain road link. In previous research, deterministic queuing models are often used for traffic flow modeling. However, due to the random environment of traffic flow, it is necessary to introduce stochastic elements into current traffic flow modeling. In our research, we use stochastic queuing models, such as Markov-modulated queuing systems, for traffic flow modeling under incidents. And non-recurrent and recurrent congestion models will be combined together to improve travel time estimation.;Man-made emergencies in the infrastructure are terrorist attacks, suicide bombings, etc. Human casualties are the major goal of intelligent adversaries. We use game theory in order to allocate first responders' resources inside the transit infrastructure to minimize human casualty. In the static zero-sum game model, we show that both the adversary and the first responder choose the same group of locations to attack and defend. In the dynamic case when the first responder is mobile while the adversary is hidden in a cell, the equilibrium solution for the first responder becomes the best patrol policy within the infrastructure. This model utilizes partially observable Markov decision process (POMDP) in which the payoff functions depend on an exogenous people flow, thus, are time varying. People flow are modeled as an open queuing network in the infrastructure. And illustration example is shown to provide insight into the competitive nature of this game between first responder and adversary.
机译:在现代交通网络中,道路紧急情况和基础设施中的人为紧急情况会直接或间接给社会带来巨大的成本。直接成本包括由于事故延误和交通拥堵导致的运输成本,以及人为紧急情况给基础设施带来的各种风险。间接成本可能包括对社会的经济和心理影响。;道路上的突发事件包括事故,伤残车辆,恶劣的天气情况,溢出的负荷,有害物质等。在这些情况下,非经常性拥堵会减缓某些交通流量道路连接。在先前的研究中,确定性排队模型通常用于交通流建模。但是,由于交通流的随机环境,有必要在当前交通流建模中引入随机因素。在我们的研究中,我们使用随机排队模型(例如马尔可夫调制排队系统)对事件下的交通流进行建模。并且非经常性和经常性的拥堵模型将被组合在一起以改善旅行时间估计。基础设施中的人为紧急情况包括恐怖袭击,自杀炸弹袭击等。人身伤亡是智能对手的主要目标。我们使用博弈论来在交通基础设施中分配急救人员的资源,以最大程度地减少人员伤亡。在静态零和博弈模型中,我们显示了对手和第一响应者都选择了相同的位置组来进行攻击和防御。在动态情况下,当第一响应者处于活动状态而对手隐藏在一个单元中时,第一响应者的均衡解决方案将成为基础结构中最佳的巡逻策略。该模型利用了部分可观察的马尔可夫决策过程(POMDP),其中回报函数取决于外来的人流,因此是时变的。人员流被建模为基础架构中的开放排队网络。并显示了示例,以深入了解此游戏在第一响应者和对手之间的竞争性质。

著录项

  • 作者

    Duan, Zhe.;

  • 作者单位

    Rutgers The State University of New Jersey - New Brunswick.;

  • 授予单位 Rutgers The State University of New Jersey - New Brunswick.;
  • 学科 Engineering Industrial.;Operations Research.;Transportation.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 105 p.
  • 总页数 105
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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