A critical problem faced by railways is how to increase capacity without investing heavily in infrastructure and impacting on schedule reliability. One way of increasing capacity is to reduce the buffer time added to timetables. Buffer time is used to reduce the impact of train delays on overall network reliability. While reducing buffer times can increase capacity, it also means that small delays to a single train can propagate quickly through the system causing knock-on delays to trains impacted by the delayed train. The Swiss Federal Railways (SBB) and Swiss Federal Institute of Technology (ETH) are researching a new approach for real-time train rescheduling that could enable buffer times to be reduced without impacting schedule reliability. This approach is based on the idea that if trains can be efficiently rescheduled to address delays, then less buffer time is needed to maintain the same level of system schedule reliability. The proposed approach combines a rescheduling algorithm with very accurate train operations (using a driver-machine interface). This paper describes the proposed approach, some system characteristics that improve its efficiency, and results of a microscopic simulation completed to help show the effectiveness of this new approach. The results demonstrate that the proposed integrated real-time rescheduling system enables capacity to be increased and may reduce knock-on delays. The results also clearly showed the importance of accurate train operations on the rescheduling system's effectiveness
The Swiss Federal Railways in cooperation with the Swiss Federal Institute of Technology ETH has developed an integrated real-time rescheduling system to simultaneously improve rail network capacity and punctuality. The approach combines real-time rescheduling (performed after a delay or incident) with very precise train operation facilitated by providing dynamic schedule information to train drivers. This information enables train drivers to change their driving behaviour and adjust their speed based on the new schedule. This can significantly reduce the number of unnecessary decelerations or stops due to conflicts. Consequently, traffic flow is improved. In addition, also energy consumption is reduced because unintended re-accelerations are minimised. This paper describes results of an analysis performed to calculate the energy savings possible using the integrated real-time rescheduling system.
Today, most large airlines operate using a hub-and-spoke strategy. At hub airports, the carriers attempt to optimize their flight schedules to minimize passenger transfer times for connecting flights. The result is a high number of flight arrivals and departures during the peak periods but only a few movements in off-peak periods. This imbalance means that infrastructure and personnel are used inefficiently. Depeaking, which consists of spreading flights more evenly throughout the day, allows airlines and ground handlers to use their resources more efficiently. Depeaking can reduce energy consumption by reducing airport congestion. Although depeaking has been applied successfully at major hubs to relieve congestion constraints, it has not been applied specifically to reduce costs and energy use. Therefore, the goal of this study was to evaluate the cost savings potential of depeaking. The focus was on cost savings for the ground handler, because obtaining airline data was difficult, given the highly competitive state of the industry. Several depeaking scenarios were evaluated with data from Zurich Airport (Switzerland). The research shows that depeaking reduces extreme workload peaks, enables staff and equipment to be used more efficiently and thereby reduces costs. The results for Zurich Airport show that a small amount of schedule adjustment can reduce ground handling costs by approximately 8%. Under the maximum schedule adjustment scenario, depeaking could reduce costs by up to 20%. The research can be extended to include additional peak-oriented costs such as airline company costs and costs of energy, as well as revenue impacts of reduced flight connectivity.
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