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首页> 外文会议>Computers in Railways X: Computer System Design and Operation in the Railway and other Transit Systems; WIT Transactions on Built Environment; vol.88 >Optimising train priorities to support the regulation of train services with the assistance of active and deductive databases
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Optimising train priorities to support the regulation of train services with the assistance of active and deductive databases

机译：借助主动和演绎数据库，优化火车优先级，以支持对火车服务的监管

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Maximisation of revenues is a fundamental goal of any business-driven railway infrastructure company. In order to achieve this target in the context of traffic regulation, it must try to avoid delays and ensure scheduled connections. However, nominally equal delays to two different trains are not equal in value from an economic point of view in most cases. Moreover, some connections between trains might be more important in this sense than others. There are complex interdependencies and reciprocal effects in railway traffic. Considering these effects, a dispatcher must evaluate possible forms of conflict resolution and the waiting times these give rise to and select the best solution possible. This is not achievable where a time-critical conflict arises at short notice. Even closed mathematical optimisation algorithms encounter limits in the case of larger railway networks due to the enormous number of constraints to be considered. This paper will therefore propose that the optimisation process be separated from the train regulation process. Instead, economically evaluated train priorities for conflict situations are to be determined with the help of active, deductive and normative rules. Existing concepts of "smart" database management systems (DBMS) with integrated active and deductive database functionalities can be used for this application. An active DBMS allows the definition of reactions to be automatically initiated by the DBMS in response to the detection of given database-related events. A deductive DBMS allows new, deducible facts to be specified, administered and specially derived from explicitly introduced facts. Train priorities are generated and assigned in detachment from day-to-day operations for lightly and heavily disrupted railway traffic respectively. Long-term optimisation of these priorities is effected by evaluating past operational data.
机译：收入最大化是任何以业务为导向的铁路基础设施公司的基本目标。为了在交通管制的背景下实现这一目标，它必须设法避免延迟并确保预定的连接。但是，从经济的角度来看，在大多数情况下，两个不同列车的名义上相等的延误在价值上并不相等。此外，从这个意义上讲，火车之间的某些联系可能比其他联系更为重要。铁路交通中存在复杂的相互依存关系和相互影响。考虑到这些影响，调度员必须评估可能的冲突解决形式以及这些冲突产生的等待时间，并选择可能的最佳解决方案。如果在短时间内出现时间紧迫的冲突，这是无法实现的。在大型铁路网络中，由于要考虑的约束数量众多，即使是封闭的数学优化算法也遇到了限制。因此，本文将建议将优化过程与列车调节过程分开。取而代之的是，应在积极，演绎和规范性规则的帮助下确定针对冲突局势进行经济评估的火车优先事项。具有集成的活动和演绎数据库功能的“智能”数据库管理系统（DBMS）的现有概念可以用于此应用程序。活动的DBMS允许响应于对给定的数据库相关事件的检测，由DBMS自动启动反应的定义。演绎DBMS允许从显式引入的事实中指定，管理和专门导出新的，可推论的事实。火车优先级的产生和分配与日常运营分开，分别用于轻度和严重中断的铁路交通。这些优先级的长期优化是通过评估过去的运行数据来实现的。

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