scholarly journals Evaluation of Congestion Mitigation Measures for Public Transport Using Transit Assignment Model

2005 ◽  
Vol 22 ◽  
pp. 239-246
Author(s):  
Hiroshi SHIMAMOTO ◽  
Fumitaka KURAUCHI ◽  
Yasunori IIDA
Keyword(s):  
Public Transport ◽  
Mitigation Measures ◽  
Transit Assignment ◽  
Congestion Mitigation ◽  
Assignment Model

Application of smart card data in validating a large-scale multi-modal transit assignment model

2017 ◽  
Vol 10 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ahmad Tavassoli ◽  
Mahmoud Mesbah ◽  
Mark Hickman
Keyword(s):  
Smart Card ◽  
Large Scale ◽  
Transit Assignment ◽  
Assignment Model ◽  
Smart Card Data

Modelling Urban Public Transit Users' Route Choice Behaviour

2011 ◽  
pp. 134-146
Author(s):  
Yulin Lee ◽  
Jonathan Bunker ◽  
Luis Ferreira
Keyword(s):  
Public Transport ◽  
Public Transit ◽  
Route Choice ◽  
User Equilibrium ◽  
Urban Transport ◽  
Transit Assignment ◽  
The Road ◽  
Transit Route ◽  
The 1960S ◽  
Assignment Models

Public transport is one of the key promoters of sustainable urban transport. To encourage and increase public transport patronage it is important to investigate the route choice behaviours of urban public transit users. This chapter reviews the main developments of modelling urban public transit users’ route choice behaviours in a historical perspective, from the 1960s to the present time. The approaches reviewed for this study include the early heuristic studies on finding the least-cost transit route and all-or-nothing transit assignment, the bus common lines problem, the disaggregate discrete choice models, the deterministic and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models. This chapter also provides an outlook for the future directions of modelling transit users’ route choice behaviours. Through the comparison with the development of models for motorists’ route choice and traffic assignment problems, this chapter advocates that transit route choice research should draw inspiration from the research outcomes from the road area, and that the modelling practice of transit users’ route choice should further explore the behavioural complexities.

Integrated simulation-based dynamic traffic and transit assignment model for large-scale network

2020 ◽  
Vol 47 (8) ◽  
pp. 898-907 ◽  
Author(s):  
Islam Kamel ◽  
Amer Shalaby ◽  
Baher Abdulhai
Keyword(s):  
Large Scale ◽  
Traffic Assignment ◽  
Dynamic Traffic ◽  
Transit Assignment ◽  
Large Scale Network ◽  
Assignment Model ◽  
Morning Peak ◽  
Simulation Based ◽  
Scale Network ◽  
Assignment Models

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.

scholarly journals A Network-Based Model of Passenger Transfer Flow between Bus and Metro: An Application to the Public Transport System of Beijing

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Wenjing Wang ◽  
Yihong Wang ◽  
Gonçalo Homem de Almeida Correia ◽  
Yusen Chen
Keyword(s):  
Public Transport ◽  
Transit Assignment ◽  
Public Transport System ◽  
Points Of Interest ◽  
Smart Card Data ◽  
Network Properties ◽  
Computationally Intensive ◽  
Extensive Computation ◽  
Assignment Models ◽  
Transfer Flow

In a multimodal public transport network, transfers are inevitable. Planning and managing an efficient transfer connection is thus important and requires an understanding of the factors that influence those transfers. Existing studies on predicting passenger transfer flows have mainly used transit assignment models based on route choice, which need extensive computation and underlying behavioral assumptions. Inspired by studies that use network properties to estimate public transport (PT) demand, this paper proposes to use the network properties of a multimodal PT system to explain transfer flows. A statistical model is estimated to identify the relationship between transfer flow and the network properties in a joint bus and metro network. Apart from transfer time, the number of stops, and bus lines, the most important network property we propose in this study is transfer accessibility. Transfer accessibility is a newly defined indicator for the geographic factors contributing to the possibility of transferring at a station, given its position in a multimodal PT network, based on an adapted gravity-based measure. It assumes that transfer accessibility at each station is proportional to the number of reachable points of interest within the network and dependent on a cost function describing the effect of distance. The R-squared of the regression model we propose is 0.69, based on the smart card data, PT network data, and Points of Interest (POIs) data from the city of Beijing, China. This suggests that the model could offer some decision support for PT planners especially when complex network assignment models are too computationally intensive to calibrate and use.

scholarly journals DEVELOPMENT OF TRANSIT ASSIGNMENT MODEL CONSIDERING TRAVEL TIME RELIABILITY

2008 ◽  
Vol 64 (4) ◽  
pp. 531-541
Author(s):  
Fumitaka KURAUCHI ◽  
Akira HARAO ◽  
Hiroshi SHIMAMOTO
Keyword(s):  
Travel Time ◽  
Travel Time Reliability ◽  
Transit Assignment ◽  
Assignment Model

A mesoscopic transit assignment model including real-time predictive information on crowding

2016 ◽  
Vol 20 (4) ◽  
pp. 316-333 ◽  
Author(s):  
Agostino Nuzzolo ◽  
Umberto Crisalli ◽  
Antonio Comi ◽  
Luca Rosati
Keyword(s):  
Real Time ◽  
Transit Assignment ◽  
Predictive Information ◽  
Assignment Model
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