Application of Dwell Time Functions in Transit Assignment Model

Abstract

The transit assignment process applied as part of the development of the Tehran transportation model is described. The process includes development of various models for dwell time as a function of transit volume. Dwell time is the time a transit vehicle spends at a stop to allow passengers to alight and board. This method was implemented by using EMME/2 transportation planning software. The calculation of dwell time is necessary in modeling transit assignment because an accurate estimation of dwell time will lead to more precise transit assignment results. The area analyzed in the model comprises various transportation analysis zones in the city of Tehran. The model output was shown to be statistically significant. Calculations were found to be valid when compared with observed data.Population growth on one hand and physical limitations of resources and constraints on the other hand have hindered further expansion of road network systems of cities around the world. As a result, cities are focusing on improving their public transit systems. This requires more accurate modeling to better replicate the systems. An important element of any transit system is dwell time, the time a transit vehicle spends at a stop to allow passengers to alight and board. An accurate estimation of dwell time can improve the reliability of transit assignment. Also, by generating accurate results for dwell time, an analyst can improve the transit system by reducing delay. Estimation of dwell time, however, historically has received little attention in transit modeling. This study focuses on a new approach to simulate dwell time at stops. The method used is applicable in studies in which transit assignment is part of the modeling process and allows forecasting dwell time at stops in the transit network.The proposed method was developed and tested in Tehran, the capital of Iran, as part of a comprehensive transportation plan. Through this comprehensive study, the first multimodal transportation model was developed, along with many submodels. The major challenges were that most elements of the model had to be developed from scratch, coupled with the large scale of the study area and lack of suitable data. Also, the model had to be compatible with local needs. Tehran has a population of 7 million spanning an area of more than 600 km 2 . The model area includes peripheral cities as well (1). EMME/2 transportation planning computer software was used in developing the model. Both the automobile and transit network systems were coded into EMME/2. This model has been used to evaluate alternative transportation plans.The transit assignment model option in EMME/2 is based on the concept of optimal strategy. An optimal strategy (2) is composed of the transit routes that minimize the expected auxiliary transit, wait, and in-vehicle time for any transit trip from an origin to a destination. Auxiliary transit is referred to as a mode of transportation used for access or egress from the transit lines or for transfers from one line to another. Travel tim...

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