Multimodal dynamic journey-planning

Abstract

In this paper, a new model, known as the multimodal dynamic timetable model (DTM), is presented for computing optimal multimodal journeys in schedule-based public transport systems. The new model constitutes an extension of the dynamic timetable model (DTM), which was developed originally for a different setting (unimodal journey-planning). Multimodal DTM demonstrates a very fast query algorithm that meets the requirement for real-time response to best journey queries, and an ultra-fast update algorithm for updating the timetable information in case of delays of scheduled-based vehicles. An experimental study on real-world metropolitan networks demonstrates that the query and update algorithms of Multimodal DTM compare favorably with other state-of-the-art approaches when public transport, including unrestricted-with respect to departing time-traveling (e.g., walking and electric vehicles) is considered.