Development of passenger flow time (PFT) model for light rail transit (LRT) users at KL Sentral Malaysia - Hor, Peay San (2018)
Dwell time is a key parameter of system performance, service reliability and quality in any mode of public transportation and represents a significant portion of the total trip time along a serviced transit line. One major component of dwell times is the alighting and boarding time of passengers, also known as passenger flow time (PFT). This mainly depends on the number of passengers alighting and boarding and the speed they do it. In Malaysia, there has yet to be an extensive study conducted on the alighting and boarding process in urban rail services. Thus, the aim of this research is to develop a predictive model to estimate the PFT through a train door of light rail transit (LRT) at KL Sentral. With this model, the main factors affetcting the PFT at a door and characteristics of the process of alighting and boarding were able to be identified. Data collection for this research was conducted both empirically and experimentally. Empirical data was collected at KL Sentral LRT station during peak hours (07:00 to 09:00 hrs) and non-peak hours (17:00 to 19:00 hrs) for a period of one week. Observations show that passengers at KL Sentral behave differently in the way they alight and board the train during peak and non-peak hours. Results reveal that the main factors affecting the PFT at a train door are the volume of alighters and boarders and the level of crowdedness in the train. It was also found that it is more relevant to apply separate models for peak hour and non-peak hours of the LRT passengers due to the different ways of alighting and boarding the train. With the models developed using the experimental approach and calibrated with the empirical data, the models proved to be significant in estimating the PFT of LRT users at KL Sentral. This will enable the rail service operator to estimate the optimum dwell time for passengers to alight and board the train during peak and non-peak hours. Besides, they can estimate the frequency of the train during peak and non-peak hours to ensure the maximum efficiency and effectiveness of the LRT system.