Abstract
Subway station dwell time (subway SDT) is used by transit agencies in determining scheduling, capacity, emissions, and cost. Currently, most use a static subway SDT value that is not responsive to changes in demand, weather, location, and users’ actions. The current research addressed these shortcomings by estimating a regression model that quantifies the impact of these variables on subway SDT. The research also introduced the concept of user-induced SDT delay, defined as any additional time it takes a subway to depart due to a passenger intentionally or unintentionally preventing the doors from closing. User-induced delay was found to increase SDT by 3.7 seconds. Furthermore, a Probit model was estimated that quantified the factors that increase the likelihood that a subway will experience user-induced delay at a given station. These factors include; an increase in boarding/alighting time and decreases in passenger arrival rate, time before doors open, and outdoor air temperature.
Acknowledgements
The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policies of any of the agencies referenced in the paper, nor do the contents constitute a standard, specification, or regulation.
Disclosure statement
No potential conflict of interest was reported by the author(s).