2016International Journal of RailwayOpen access

Calibration of Timetable Parameters for Rail-Guided Systems

Weiting Zhao, Ullrich Martin, Yong Cui, Maureen Kosters

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Abstract

In order to achieve a comprehensive utilization of railway networks, it is necessary to accurately assess the timetable indicators that effect the train operation. This paper describes the parameter calibration for two timetable indicators: scheduled running time and scheduled dwell time. For the scheduled running time, an existing model is employed and the single timetable parameter (percentage of minimum running time) in that model is optimized. For the scheduled dwell time, two intrinsic characteristics: the significance of stations and the average headway at each station are proposed firstly to form a new model, and the corresponding timetable parameters (the weight of the significance and the weight of the average headway) are calibrated subsequently. The Floyd Algorithm is used to obtain the connectivity among stations, which represents the significance of the stations. A case study is conducted in a light rail transportation system with 17 underground stations. The results of this research show that the optimal value of the scheduled running time parameter can be automatically determined, and the proposed model for the scheduled dwell time works well with a high coefficient of determination and low relative root mean square error through the leave-one-out validation.

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In order to achieve a comprehensive utilization of railway networks, it is necessary to accurately assess the timetable indicators that effect the train operation. This paper describes the parameter calibration for two timetable indicators: scheduled running time and scheduled dwell time. For the scheduled running time, an existing model is employed and the single timetable parameter (percentage of minimum running time) in that model is optimized. For the scheduled dwell time, two intrinsic characteristics: the significance of stations and the average headway at each station are proposed firstly to form a new model, and the corresponding timetable parameters (the weight of the significance and the weight of the average headway) are calibrated subsequently. The Floyd Algorithm is used to obtain the connectivity among stations, which represents the significance of the stations. A case study is conducted in a light rail transportation system with 17 underground stations. The results of this research show that the optimal value of the scheduled running time parameter can be automatically determined, and the proposed model for the scheduled dwell time works well with a high coefficient of determination and low relative root mean square error through the leave-one-out validation.

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Available abstract

In order to achieve a comprehensive utilization of railway networks, it is necessary to accurately assess the timetable indicators that effect the train operation. This paper describes the parameter calibration for two timetable indicators: scheduled running time and scheduled dwell time. For the scheduled running time, an existing model is employed and the single timetable parameter (percentage of minimum running time) in that model is optimized. For the scheduled dwell time, two intrinsic characteristics: the significance of stations and the average headway at each station are proposed firstly to form a new model, and the corresponding timetable parameters (the weight of the significance and the weight of the average headway) are calibrated subsequently. The Floyd Algorithm is used to obtain the connectivity among stations, which represents the significance of the stations. A case study is conducted in a light rail transportation system with 17 underground stations. The results of this research show that the optimal value of the scheduled running time parameter can be automatically determined, and the proposed model for the scheduled dwell time works well with a high coefficient of determination and low relative root mean square error through the leave-one-out validation.

Key concepts: Headway, Dwell time, Calibration, Engineering, Simulation, Real-time computing, Reliability engineering, Statistics

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