Optimization of Timetable Supplement from a Passenger Based Socio-Economic Point of View
Keywords:timetable supplement, train delays, passenger delay model, optimization, socio-economic, cost-benefit analysis, upgrade of Sydbanen
This article discusses how to optimize the timetable supplement in timetables. The focus of this article will be on railways, but the principle will in theory apply to all transportation modes within the area of public transportation.
When constructing timetables it is important to plan the right amount of timetable supplement. Too little timetable supplement will result in many delays, while too high timetable supplement will result in a (too) high planned travel time which will affect every departure whether or not the train is delayed. At present timetable supplement is chosen based on experience or estimates. Through an optimization process it is possible to find the optimal timetable supplement. A way to do so is by using the passenger delay model in a socio-economic analysis as done by (Thorhauge & Piester, 2010). In this process the train delays (or a simulation of the train delays) are needed. The overall process is (if the train delays are not already known):
Simulation of train delays → modeling passenger delays → estimation of the socio-economic effects
A case study of an upgrade of Sydbanen between Ringsted and Rødby has been conducted using the passenger delay model and the methods are described in this article. The case study has shown that the optimum timetable supplement is between 6-9 % depending on the scenario. By optimizing the timetable supplement it is possible to achieve a surplus of 250-500 mio. DKK during the evaluation period compared to the proposed timetable by the Danish Transport Authority (Trafikstyrelsen, 2008). Note however that none of the investigated scenarios are socio-economic viable even though the timetable and timetable supplement is optimized.
Note that this paper is regarded as a sequel to the article “The usability of passenger delay models in socio-economic analysis” (Thorhauge, 2010). This article is based on the results of (Thorhauge & Piester, 2010).