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.
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