Abstract
In urban areas transportation demand is commonly served both by private cars and mass transit systems (bus, tram, metro, etc.), which are usually based on a network of partially competing and overlapping lines. Therefore, user pre-trip path choice behaviour in transit systemsrefers to overall strategies that specify which line will be boarded at each bus stop (more generally how the user will behave at diversion nodes). The topology of user strategies are effectively modelled by hyperpaths (introduced by Nguyen and Pallottino, 1988). The pre-trip choice among hyperpaths (say strategies) is currently simulated through a deterministic choice model. This assumption leads to deterministic network loading or user equilibrium assignment for uncongested or congested network respectively. In this paper the pre-trip choice among hyperpaths is simulated through probabilistic choice models derived from random utility theory. Resulting stochastic network loading and user equilibrium models are analysed as well as solution algorithms. Results of an application to a test system and a real one are also reported, using different perceived cost distribution.
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Cantarella, G.E., Vitetta, A. (2001). Stochastic assignment to high frequency transit networks: models, algorithms, and applications with different perceived cost distributions. In: Pursula, M., Niittymäki, J. (eds) Mathematical Methods on Optimization in Transportation Systems. Applied Optimization, vol 48. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3357-0_7
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DOI: https://doi.org/10.1007/978-1-4757-3357-0_7
Publisher Name: Springer, Boston, MA
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