There are very large transport demands for commuter lines in Japan, where trains are operated at very high frequencies. In metropolitan areas, for example, the train headway is about two or three minutes in the morning. Furthermore, stations are routinely crowded with passengers, and trains often dwell for longer times than scheduled. In this situation, trains approaching a station are often forced to decelerate or stop between stations. This phenomenon easily occurs especially where the train headway makes a bottleneck. Once a train stops between stations, the running time of the train increases and recovery from traffic disruption delays. From the viewpoint of energy consumption, the occurrence of this phenomenon is also undesirable because trains may repeat unexpected acceleration and deceleration. One of the train control methods to solve the problem is to avoid unnecessary stops with the headway kept as short as possible. To realise this control, detailed information on the running status of the preceding train is necessary. In the conventional railway system, on the other hand, the information given to trains to control its speed is only signal aspects. Therefore, it is difficult to control trains to run at the optimal speed adapted to the traffic status. We are now studying a new train and traffic control system with which railway sub-systems such as rolling stock, electric power supply system, traffic control system and signalling system, co-operate based on the information about train movement and traffic). In this paper, we describe the train control method which is a core function of the new system. The control method named 'prediction control' is based on the information of predicted time when the train departs from a station. To evaluate the effects of proposed control method, we carried out computer simulations of traffic and an electrical feeding circuit. As a result, it has been proved that the new method reduces the train stopping time between stations and the electric energy consumption at substations.
Advanced train and traffic control based on prediction of train movement
Fortschrittliche Eisenbahn- und Verkehrssteuerung auf Basis der Prädiktion der Zugbewegung
2004
6 Seiten, 14 Bilder, 6 Quellen
Aufsatz (Konferenz)
Englisch
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