A parallel set-based model on the shortest travel time in long-distance transportation systems

Abstract

The shortest travel time in long-distance transportation systems (LDTS) is a key indicator for measuring regional connectivity and mapping accessibility at national and global levels. For traditional methods, it is a great challenge to calculate the shortest travel time with millions of origin-destination pairs and evaluate the overall performance. To fill this technique gap, this study proposed a novel model to get all the trips with different numbers of transfers through a series of set-based methods and then calculate all the shortest travel time between stops. The set-based model was tested for calculating the shortest travel time in LDTS of China. Using the optimization algorithm, we can significantly reduce the number of transfer trips that need to be calculated. For instance, the number of transfer trips decreased by 96.17%, 98.15%, and 79.02%, for conventional railway, high-speed railway, and air transportation, respectively, when the number of transfers was two. The set-based model can be extended to calculate the door-to-door travel time between places, for instance, mapping the fine-scale accessibility at the national level. Furthermore, we proved that this set-based model, proposed in this study, could also be parallelized and applied to any other LDTS in the General Transit Feed Specification format.