Integrated Demand and Capacity Management for Cabin-Based Transport Systems

Cabin-based transport systems (e.g., cable cars, subways) are of increasing importance for public transport systems. To satisfy the passengers (effectiveness) as well as the operators (efficiency) requirements the passenger flow to cabins has to be managed. State-of-the art access control might be described as laissez faire access management, i.e., there is no access management because at each station the cabin might be loaded up to the maximum available capacity. Therefore, at peak hours, undesirable situations may occur, if only fully loaded cabins arrive at the next station, i.e., the passengers may have to wait quite long although the queue length is short. From the perspective of the transport system operator, it is optimal to maximize the system throughput but some of the customers are treated unfairly in this case. The objective of this study is to develop and evaluate alternative access policies to reduce overall passenger waiting times and to improve “fairness”. For this purpose, we build a discrete event simulation model that is based on empirical data. This model will be used to analyse the robustness of the developed access policies under consideration of stochastic input variables (e.g., demand distribution, access behaviour of passengers, etc.). The results show that it is not possible to reduce the waiting time in a given station without managing the passenger access of the previous ones. It is necessary to (re)balance the capacity at all stations, e.g., passengers at one station wait longer in order to reduce waiting time of the subsequent stations.