  We present multimodal DTM, a new model for multimodal journey planning in
public (schedule-based) transport networks. Multimodal DTM constitutes an
extension of the dynamic timetable model (DTM), developed originally for
unimodal journey planning. Multimodal DTM exhibits a very fast query algorithm,
meeting the request for real-time response to best journey queries and an
extremely fast update algorithm for updating the timetable information in case
of delays. In particular, an experimental study on real-world metropolitan
networks demonstrates that our methods compare favorably with other
state-of-the-art approaches when public transport along with unrestricted
w.r.t. departing time traveling (walking and electric vehicles) is considered.
