A decision support tool for capacity designing of BRT stations using discrete-event simulation

[摘要] ENGLISH ABSTRACT: The purpose of this study is to investigate the capacity of a proposed bus rapid transit (BRT) station in Cape Town. A bus rapid transit system is a high-capacity public transportation system that carries passengers from one point to another, providing a service that is faster and more efficient than an ordinary bus line. The implementation of these systems is increasing rapidly worldwide, serving as a solution to decrease traffic congestion.The capacity of the proposed bus station, known as the Thibault Station, is investigated in the study by developing a simulation model. The aim is to develop a stochastic simulation model, which represents the flow of passengers throughout the station so that the station capacity can be investigated. By developing a stochastic model as opposed to a deterministic model, elements of uncertainty can be included into the model, thereby representing a system that is closer to the real-life situation under investigation. The majority of BRT systems, as well as past studies undertaken on the Thibault Station, are designed using deterministic calculations.The study commences by researching literature on BRT systems and focuses on the current methods used to calculate station capacity requirements. Thereafter, the concept of simulation is introduced. Simulation is the method chosen to model and evaluate the passenger and bus operations at the Thibault Station.The study presents the methods used to build and verify the simulation model. This is done to familiarise the user with a number of aspects of the model. The model can then be used as a tool to investigate capacity parameters and alternative designs or scenarios. Using the results of these investigations, decisions can ultimately be made regarding the planning and design components of any bus rapid transit station given that the model is adapted.Scenario results, as well as interpretations of performance measurements, are presented at the end of the study. The results can be used for more realistic design of BRT stations using stochastic modelling.

[发布机构] Stellenbosch University