Open access
Date
2019-05Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Public transport networks such as bus and railway networks are highly complex systems. In fact, multiple sources of uncertainty including fluctuating passenger demand, variable road and traffic conditions, weather, and technical failures affect the network performance and reliability. These uncontrollable, stochastic factors follow intricate dynamics in space and time that makes it difficult to incorporate them into important decision-making processes of traffic management. For example, understanding how delays evolve (fade out absorbed by available buffer times,remain the same, or propagate through the network) is critical to undertake correct rescheduling actions for vehicles in the presence of delays or disruptions. Moreover, the number of stochastic factors is usually very large due to the many moving units or network links, which poses further modeling challenges. Goal of this paper is twofold. First, we review the existing stochastic models of the uncertainty employed in the public transport optimization literature, underlying their merits and shortcomings. Second, we define a roadmap for modeling high-dimensional uncertainties in public transport networks in a sound manner, with the goal of incorporating this uncertainty into stochastic optimization approaches. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000342827Publication status
publishedPublisher
STRCEvent
Subject
Railway and bus networks; Uncertainty dynamics; Stochastic processes; Stochastic optimizationOrganisational unit
09611 - Corman, Francesco / Corman, Francesco
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
Notes
Conference lecture on 15 May 2019.More
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ETH Bibliography
yes
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