Methods for quantitative assessment of passenger flow influence on train dwell time in dense traffic areas

Sélim Cornet (1) , Christine Buisson (2) , François Ramond (3) , Paul Bouvarel (1) , Joaquin Rodriguez (2)

1 SNCF Réseau [La Plaine st Denis]
2 IFSTTAR/COSYS - Département Composants et Systèmes
3 SNCF : Innovation & Recherche

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 system during the dwelling process. This paper proposes an approach for estimating the minimum dwell time knowing the numbers of alighting, boarding and on board passengers, using Automatic Vehicle Location and Automatic Passenger Counting data. Based on the knowledge of this value, a method for estimating the conditional distribution of dwell time given passenger flows is presented. Numerical experiments are carried out on two stations located inside the dense traffic area of Paris suburban network. The obtained results show a broad applicability of these methods, that hence seem very promising.

Domaines: Modélisation et simulation

Sélim Cornet, Christine Buisson, François Ramond, Paul Bouvarel, Joaquin Rodriguez. Methods for quantitative assessment of passenger flow influence on train dwell time in dense traffic areas. 2018. ⟨hal-01909708v1⟩