Analysis of Passenger Waiting Time in Metro Stations by Using Simulation Techniques.

With the increasing demand for public transportation due to congested city highways and streets, the rail systems and especially metro have become one of the most viable alternatives for daily commuting. While city planners are excited with the increasing public transportation rider ship, they are also challenged with a higher volume of passenger flow and longer queuing lines at the existing stations and of course, metro platforms.One of the most useful features to improve the current situation and plan for the future, is using simulation tools to help the planner how to evaluate system operation design, queue management, fare equipment design and fare policy impacts, all in virtual and dummy world.In this study, Co- ordination of headways between entrance of passengers to metro station, and arrival of metro trains that travel by fixed scheduling is proposed. The objectives for the study, are development a simulation model to analyze the passenger waiting time of an urban metro stations with other modes of feeder services. Urban metro system is characterized by its comparatively short headway and fixed schedules. Thus, the behavior of passengers in urban metro is significantly different from the behavior of passengers in intercity train or bus system. If the entrance of passengers from other modes like buses, taxies, walking and etc. To metro station considered as a major feeder system for the urban metro, passenger waiting time and related behaviors of the urban metro station should be influenced by the reliability of train scheduling that the most important part is average headway between arrival of each metro trains.So, in this study by using simulation technique, a reliable simulation model for passenger and metro train that named as "METSIM Software", where designed.The results provide planners with an analytic model for accurately quantifying the relation between passenger waiting time of urban metro system and the reliability of other variables like headway of arrival metro trains due to fixed scheduling, passenger flow entrance rate from other feeder services to the station, fare policy and the equipment that presented at ticket hall for fare collection (like ticket vending machine, waiting in queue lines for buying paper tickets or credit cards, and ticket acceptance gates).