Transit Assignment Model Incorporating Bus Dwell Time

Author(s):  
Leilei Sun ◽  
Qiang Meng ◽  
Zhiyuan Liu
Author(s):  
Hedayat Z. Aashtiani ◽  
Hamid Iravani

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.


2017 ◽  
Vol 10 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ahmad Tavassoli ◽  
Mahmoud Mesbah ◽  
Mark Hickman

2020 ◽  
Vol 47 (8) ◽  
pp. 898-907 ◽  
Author(s):  
Islam Kamel ◽  
Amer Shalaby ◽  
Baher Abdulhai

Although the traffic and transit assignment processes are intertwined, the interactions between them are usually ignored in practice, especially for large-scale networks. In this paper, we build a simulation-based traffic and transit assignment model that preserves the interactions between the two assignment processes for the large-scale network of the Greater Toronto Area during the morning peak. This traffic assignment model is dynamic, user-equilibrium seeking, and includes surface transit routes. It utilizes the congested travel times, determined by the dynamic traffic assignment, rather than using predefined timetables. Unlike the static transit assignment models, the proposed transit model distinguishes between different intervals within the morning peak by using the accurate demand, transit schedule, and time-based road level-of-service. The traffic and transit assignment models are calibrated against actual field observations. The resulting dynamic model is suitable for testing different demand management strategies that impose dynamic changes on multiple modes simultaneously.


2008 ◽  
Vol 64 (4) ◽  
pp. 531-541
Author(s):  
Fumitaka KURAUCHI ◽  
Akira HARAO ◽  
Hiroshi SHIMAMOTO

2016 ◽  
Vol 20 (4) ◽  
pp. 316-333 ◽  
Author(s):  
Agostino Nuzzolo ◽  
Umberto Crisalli ◽  
Antonio Comi ◽  
Luca Rosati

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