Development of High-Speed Railway Travel Assignment Algorithm based on Station Choice Probability

The travel assignment is a step of loading inter-zonal trips in the traditional travel demand forecasting model, and the optimal strategy algorithm is used the most to assign railway trips. The algorithm has a limitation that trips are con¬centrated from one zone to one station. Therefore, this study aims to develop a high-speed rail travel assignment algorithm considering station choice probabilities by high-speed railway station using O/D and network data from the Korea Trans¬port Database (KTDB). The distance between the centroid and high-speed railway stations and the train frequency at the stations are considered as independent variables, and the algorithm is developed to estimate station choice probability and high-speed railway travel volume. The prediction results are superior to those of the existing optimal strategy algorithm for major stations. The proposed algorithm will be used to predict high-speed railway travel in regions influenced by several high-speed railway stations.