Transit Assignment Model Incorporating Bus Dwell Time

Sun, Lanlan; Meng, Qiang; Liu, Zhiyuan

doi:10.3141/2352-09

Cited by 12 publications

(5 citation statements)

References 18 publications

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“…More recently, [26] proposed an assignment model in which dwell times are modeled as the maximum of the boarding and alighting time (as if they happened simultaneously through different doors). They applied the transit equilibrium model proposed by [9] and used a revised optimal strategy algorithm and a modified MSA, called Method of Successive Weighted Averages (MSWA) [24] to solve the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

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A congested and dwell time dependent transit corridor assignment model

Alonso

Muñoz

Ibeas

et al. 2016

J of Advced Transportation

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This research proposes an equilibrium assignment model for congested public transport corridors in urban areas. In this model, journey times incorporate the effect of bus queuing on travel times and boarding and alighting passengers on dwell times at stops. The model also considers limited bus capacity leading to longer waiting times and more uncomfortable journeys. The proposed model is applied to an example network, and the results are compared with those obtained in a recent study. This is followed by the analysis and discussion of a real case application in Santiago de Chile. Finally, different boarding and alighting times and different vehicle types are evaluated. In all cases, demand on express services tends to be underestimated by using constant dwell time assignment models, leading to potential planning errors for these lines. The results demonstrate the importance of considering demand dependent dwell times in the assignment process, especially at high demand levels when the capacity constraint should also be considered.

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Section: Literature Reviewmentioning

confidence: 99%

“…Under different boarding and alighting conditions (i.e. simultaneous processes) expression ( 15) should be adjusted accordingly [26]. However, behavior in transit corridors equipped with off-board fare payment stations is very often similar to metro systems, where alighting users precede boarding.…”

Section: Cost Function With Capacity Constraintmentioning

confidence: 99%

A congested and dwell time dependent transit corridor assignment model

Alonso

Muñoz

Ibeas

et al. 2016

J of Advced Transportation

View full text Add to dashboard Cite

show abstract

“…Referring to passenger route choices, train delays has been considered as an influence factor [ 5 – 7 ]. Moreover, the analysis of passenger travel behaviors is considerably important [ 8 ]. Zhu (2011) [ 9 ] studied a scenario-based route choice model and calculation method against the background of the 2010 World Expo in Shanghai, China.…”

Section: Introductionmentioning

confidence: 99%

The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory

Wang

Jia

2017

PLoS ONE

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Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson’s Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

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“…The common line problem refers to the route choice problem at transit stops served by several competing transit lines. To address this problem, there are two methods distinguished by their network representations: the hyperpath graph network representation (Nguyen and Pallottino 1988, Wu et al 1994, Cominetti and Correa 2001, Hamdouch et al 2004, Gentile et al 2005, Hamdouch and Lawphongpanich 2008, Corté s et al 2013, Sun et al 2013, Hamdouch et al 2014, Li et al 2015, Oliker and Bekhor 2018, Xu et al 2020) and the route-section network representation (de Cea and Ferná ndez 1993;Lam et al 1999, Nielsen 2000, Lam et al 2002, Teklu 2008, Szeto et al 2011a, Leurent 2012, Szeto et al 2013, Jiang and Szeto 2016, Sun and Szeto 2018.…”

mentioning

confidence: 99%

Reliability-based equitable transit frequency design

Jiang

2021

Transportmetrica A: Transport Science

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Fairness is an important criterion for achieving sustainable urban development, and thus, is of major concern in providing public transport services. While most existing studies focus on accessing or evaluating the fairness condition of a given transit network, this study explicitly incorporates fairness as an objective in the planning step to allocate a fleet to a set of bus lines. A multi-objective bilevel programming model is developed for the transit frequency setting problem. The lower level problem is the reliability-based transit assignment problem that captures the effects of supply-side uncertainty on passengers' route choice behaviour via the concept of travel time budget referred to as effective travel cost. The upper level problem is to determine optimal frequency settings to simultaneously minimise the total effective travel cost and maximise the network fairness condition, measured by minimum reduction in effective travel cost of all Origin-Destination (OD) pairs. A multi-objective Artificial Bee Colony algorithm (MOABC) is developed to solve the bilevel model, where non-dominated solutions are maintained by a predefined external archive. Numerical studies find that: 1) increasing the frequency may not improve the fairness condition; 2) there is a tradeoff between the objective of minimising total effective travel cost and that of maximising the fairness measurement; 3) the two objectives can be improved simultaneously using a large fleet; 4) the effect of passengers' risk aversion attitude on the fairness measurement depends on the frequency setting; it could either amplify the fairness measurements or have no impact.

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Transit Assignment Model Incorporating Bus Dwell Time

Cited by 12 publications

References 18 publications

A congested and dwell time dependent transit corridor assignment model

A congested and dwell time dependent transit corridor assignment model

The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory

Reliability-based equitable transit frequency design

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