Evaluating Two Capacity Simulation Tools on Shared-Use U.S. Rail Corridor
Hamed Pouryousef, Pasi Lautala
Abstract
Hamed Pouryousef, Pasi Lautala
Abstract
Most passenger rail services in the United States (U.S.) operate on corridors that are shared with freight traffic. As the demand for passenger and freight transportation grows and emphasis is placed on increased speed and on-time performance of passenger services, the available capacity becomes even more consumed. When higher speed passenger trains are mixed with freight, the increased heterogeneity from expanding speed differential creates further challenges for reliable operations. Based on the experiences in the other parts of the world (particularly in European rail corridors), the required density and reliability is typically secured through structured/planned/scheduled operations instead of the unstructured, or improvised, operations philosophy that is currently prevalent in the U.S. There are several tools and methodologies available in both the European and U.S. rail environments that utilize user defined infrastructure specifications, operational rules, signaling systems and rolling stock characteristics to evaluate capacity. This paper introduces the main components of two simulation software packages, U.S. developed Rail Traffic Controller (RTC) and European RailSys, and applies them both to a shared-use case study corridor in the U.S. The outputs from each package are compared and the non-timetable based software output (RTC) is applied in the timetable based software (RailSys) as input to form a hybrid model that allows the utilization of timetable compression techniques. The research revealed that simulation outputs from both software packages are very similar, if the trains can be operated according to initial arrival/departure times on the corridor. However, RTC’s database and timetable parameters are easier to implement, while RailSys has more timetable management features and options that can be used to improve an existing timetable when introducing new trains running along the corridor.
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Most passenger rail services in the United States (U.S.) operate on corridors that are shared with freight traffic. As the demand for passenger and freight transportation grows and emphasis is placed on increased speed and on-time performance of passenger services, the available capacity becomes even more consumed. When higher speed passenger trains are mixed with freight, the increased heterogeneity from expanding speed differential creates further challenges for reliable operations. Based on the experiences in the other parts of the world (particularly in European rail corridors), the required density and reliability is typically secured through structured/planned/scheduled operations instead of the unstructured, or improvised, operations philosophy that is currently prevalent in the U.S. There are several tools and methodologies available in both the European and U.S. rail environments that utilize user defined infrastructure specifications, operational rules, signaling systems and rolling stock characteristics to evaluate capacity. This paper introduces the main components of two simulation software packages, U.S. developed Rail Traffic Controller (RTC) and European RailSys, and applies them both to a shared-use case study corridor in the U.S. The outputs from each package are compared and the non-timetable based software output (RTC) is applied in the timetable based software (RailSys) as input to form a hybrid model that allows the utilization of timetable compression techniques. The research revealed that simulation outputs from both software packages are very similar, if the trains can be operated according to initial arrival/departure times on the corridor. However, RTC’s database and timetable parameters are easier to implement, while RailSys has more timetable management features and options that can be used to improve an existing timetable when introducing new trains running along the corridor.
Key concepts: Train, Transport engineering, Software, Rail freight transport, Simulation software, Computer science, Engineering, Operations research