The dynamic interaction between passenger flows and rail service

Rail and metro networks are nowadays the backbone of public transportation systems especially in high density contexts. Due to the constant increase in travel demand, rail systems are more and more dense and service providers have the difficult task of planning a timetable which has to be robust and stable. Moreover, in order to increase customers??? satisfaction, it is necessary to provide sufficient transport capacity avoiding train and platform congestion and guaranteeing a good level of service quality. To reach this target, an appropriate timetable evaluation, which expresses the interactions between train operation and passenger flows, is essential. In particular, the aim of the paper is to analyse the dynamic effect of dwell time at station on the service in the case of metro networks. In fact, above all in crowded situations, train can be forced to remain stopped in a station more time than what has been planned, causing a delay. As a consequence, the more a train is delayed, the more the passengers arrive at the station and get on the train further increasing the dwell time. The evaluation of this dynamic effect, known in the literature as ???snowball effect???, provides an analysis of the timetable which is as closely as possible to the real phenomenon and, above all, yields an estimation of the effective congestion of carriages. Hence, by adopting suitable indexes which reflect passenger experiences of the service, it is possible to establish an appropriate evaluation method for planning train operations. An application on a real metro line in the city of Naples (Italy) has been applied in order to show the utility of the proposed approach