|Publication type:||Conference paper|
|Type of review:||Peer review (publication)|
|Title:||A multi-component closed-loop control framework for rail traffic networks|
|Authors:||Wüst, Raimond Matthias|
|Conference details:||12th Swiss Transport Research Conference, Ascona, 2-4 May 2012|
|Subjects:||Network performance; Real-time dispatching; Rail traffic simulation; Rail traffic state monitoring|
|Subject (DDC):||370: Education|
|Abstract:||The operation of rail transport systems has become an increasingly challenging task over the last decades. One of the main reasons is the conflict between the surge in passenger and freight demand and the capacity constraints of the railway system (on railway lines and at railway stations). To allow for a better understanding of the system dynamics in different operational states (including disruptions) and to have improved control strategies at hand, a multi-component simulation framework, representing an entire closed-loop operation environment for railway networks is currently under way. Based on this framework, railway network operators shall be enabled to investigate timetable and scenario generation, railway traffic operations, operational decision support, and operational performance criteria. In addition, the architecture of the framework shall allow for investigating the effects of moving from a distributed, event driven train control system (where involved operational parties are only weakly interacting) towards an increasingly integrated, time controlled and automated operational concept. This concept of tight time control requires all operational processes to be continuously monitored with respect to the production schedule. Deviations exceeding some pre-determined tolerance thresholds will results in a re-adjustment of the production plan in real-time. A dedicated rescheduling algorithm will be implemented to achieve this goal. This algorithm is based on a resource-constrained multi-commodity flow model for conflict-free train scheduling recently developed at ETH Zurich. To explicitly take into account the various parties (agents) involved, the system can be configured such that the agents behave according to existing or virtual profiles. For instance, train drivers might be technically enabled to follow new operational targets like re-adjusted train speeds while approaching conflict points. With this framework, scenarios for different operational and technical conditions as well as for internal and/or external disturbances can be investigated and the differences in performance with respect to customer satisfaction can be evaluated (represented for example by the overall train delay, cumulated passenger delays or timely availability of customer information). The framework, called Rail Transport Service Environment (RTSE), consists of three main modules: (i) a traffic simulation environment, (ii) a system state monitoring module, and (iii) the rescheduling algorithm mentioned above. The modules are interconnected through standard communication interfaces so that each module can be exchanged easily depending on the user environment. Railway traffic simulations are carried out using the dedicated railway simulation tool OpenTrack. The tool is used by various train operation and train infrastructure companies in order to test, amongst others, the feasibility of timetables or signalling scenarios. The simulated traffic scenarios will be interpreted by an automated monitoring module (including some threshold detection mechanism, where the thresholds depend on the operational policies, etc.), which compares actual and planned process states and induces rescheduling actions executed by the rescheduling algorithm, if required. Those rescheduling actions result in new (adjusted) state space plans, which take into account changes in process states and the eventually reduced availability of resources.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Appears in collections:||Publikationen School of Engineering|
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