Incorporating personalization and bounded rationality into stochastic transit assignment model

2021 ◽  
Vol 127 ◽  
pp. 103127
Author(s):  
Yu Jiang ◽  
Avishai (Avi) Ceder
Keyword(s):  
Bounded Rationality ◽  
Transit Assignment ◽  
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

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 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

scholarly journals Research on the Multiroute Probit-Based Public Transit Assignment Model Based on Bus Stop

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Zhenyu Mei ◽  
Dianhai Wang ◽  
Fujian Wang ◽  
Jun Chen ◽  
Wei Wang
Keyword(s):  
Road Network ◽  
Road Traffic ◽  
Public Transit ◽  
Transit Assignment ◽  
Transit Network ◽  
Assignment Model ◽  
Trip Time ◽  
Resistance Function ◽  
Assignment Models ◽  
The Relationship

A public transit network differs from a general road network. The passenger flow of bus stops and the limited capacity of buses have a greater effect than road traffic flow on the running time of buses. As a result, conventional public transit assignment models that adopt the econometric road network path concept have numerous limitations. Based on the analysis, the generalized bus trip time chain is analyzed, and the concept of a congestion function is proposed to describe the relationship between trip resistance and flow in the current paper. On the premise of this study, the transit network resistance function is formed and the multiroute probit-based loading model is established. With using STOCH or Dial's algorithm, the process of distribution is proposed. Finally, the model is applied to the transit network assignment of Deqing Town in Zhejiang Province. The result indicates that the model can be applied to practical operations with high-precision results.

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