Methods for quantitative assessment of passenger flow influence on train dwell time in dense traffic areas
Document Type
Journal Article
Publication Date
2019
Subject Area
place - europe, place - urban, mode - rail, technology - intelligent transport systems, ridership - behaviour, planning - methods
Keywords
Railway operations, real-time management, dwell time
Abstract
Railway operations in dense traffic areas are very sensitive even to small disturbances, and thus require careful planning and real-time management. Dwell times in stations are in particular subject to a high variability and are hard to predict; this is mostly due to the interactions between passengers and the railway system during the dwelling process. This paper presents a data-driven approach for assessing the influence of the numbers of alighting, boarding and on board passengers on the dwell time. We propose to split the dwell time into a deterministic component depending on the passenger flow, called the Minimum Dwell Time, and a random component. A method for estimating the minimum dwell time is provided. Based on the knowledge of this value, observations can be classified according to the main determinant of dwell time, namely timetable constraints or passenger exchange. The latter observations are used for estimating the conditional distribution of dwell time given passenger flows. Numerical experiments are carried out on stations located inside the dense traffic area of Paris suburban network. The obtained results indicate that the presented method can be used for a variety of applications, such as capacity assessment or stochastic simulation.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
Cornet, S., Buisson, C., Ramond, F., Bouvarel, P., & Rodriguez, J. (2019). Methods for quantitative assessment of passenger flow influence on train dwell time in dense traffic areas. Transportation Research Part C: Emerging Technologies, Vol. 106, pp. 345-359.
Comments
Transportation Research Part C Home Page:
http://www.sciencedirect.com/science/journal/0968090X