Article ID Journal Published Year Pages File Type
4950094 Electronic Notes in Theoretical Computer Science 2016 21 Pages PDF
Abstract
This work is part of an ongoing effort to understand the dynamics of passenger loads in modern, multimodal transportation networks (TNs) and to mitigate the impact of perturbations. The challenge is that the percentage of passengers at any given point of the TN that have a certain destination, i.e. their distribution over different trip profiles, is unknown. We introduce a stochastic hybrid automaton model for multimodal TNs that allows to compute how such probabilistic load vectors are propagated through the TN, and develop a computation strategy for forecasting the network's load a certain time into the future.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
Authors
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