A mixed-equilibrium model of individual and household activity–travel choices in multimodal transportation networks

Vo, Khoa D.; Lam, William H. K.; Li, Zhi-Chun

doi:10.1016/j.trc.2021.103337

Cited by 8 publications

(5 citation statements)

References 86 publications

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“…Furthermore, studies have focused explicitly on the anticipated use of public transport in the post-pandemic era [46] and the travel behavior of university students who live on campus [47]. Many studies have focused on travel behavior in cities in the face of the COVID-19 pandemic [6,[46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62]. Car use might be dominant in academic communities due to similarities with urban transportation patterns.…”

Section: Review Of the Relevant Literaturementioning

confidence: 99%

Dynamics of Campus Travel Behavior under the COVID-19 Pandemic

Naaman,

Shiran,

Alavi

et al. 2023

Future Transportation

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The COVID-19 pandemic has shown to be a global challenge that, in addition to other effects, has influenced travel behavior. This study examines factors affecting academic travelers’ mode choice before and during the pandemic and factors contributing to sustainable transportation on campus. By examining their travel patterns and behaviors, we contribute to understanding transportation preferences and identifying opportunities for sustainable transportation on university campuses. Studying academic travelers is crucial as they are significant daily travelers with a substantial impact on transportation systems and the environment. Understanding their mode choices helps transportation planners and policymakers promote sustainable transportation options. The literature has identified influential factors in making trips to university campuses, including age, gender, accommodation, cost, and travel time. However, cross-sectional studies involving comprehensive variables are lacking and the influence of the COVID-19 pandemic on transportation has not been thoroughly evaluated. To address this gap, the current study aims to evaluate novel variables, including intra-transport modes, entry permits, accessibility, parking availability, occupations, level of study, travel purpose, and visit frequency. The University of Isfahan, accessible by all modes of transport, was selected as the study area. After analyzing the questionnaire and variables using SPSS software (IBM SPSS Statistics for Windows, Version 22.0 Released 2013), travel behavior was studied by discrete choice models and the models’ coefficients were estimated using NLOGIT. The finding demonstrated that using private modes (taxi, private vehicle, and active modes) increased in response to the pandemic, while using public modes (bus or subway) represented a decline. Before and during the pandemic, most people who had the same trip purpose shifted from taking the bus to using private vehicles and active transportation. Generally, people became more inclined to walk on campus during the pandemic. This study aimed to examine the travel behavior of academic travelers, who possess diverse travel choices compared with typical commuters, thus providing valuable insights into how the broader population might respond to different transportation options. The findings offer a novel perspective for university and city planners, enabling more informed decisions regarding sustainable development in campus areas.

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Section: Review Of the Relevant Literaturementioning

confidence: 99%

Dynamics of Campus Travel Behavior under the COVID-19 Pandemic

Naaman,

Shiran,

Alavi

et al. 2023

Future Transportation

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“…Vo et al . (2021) developed a novel household-oriented activity-based mixed-equilibrium model for estimating individual and household activity-travel choices in multimodal transportation networks with interactions between private car and public transit modes.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The experimental results showed that the adopted policies can reduce carbon dioxide emissions from container transportation in Bohai Rim from 3.29 to 6.70% under different scenarios. Vo et al (2021) developed a novel household-oriented activity-based mixed-equilibrium model for estimating individual and household activity-travel choices in multimodal transportation networks with interactions between private car and public transit modes. Numerical examples were provided to illustrate the model's merits and its applications for examining the effect of the coronavirus disease 2019 (COVID-19) pandemic.…”

Section: Literature Reviewmentioning

confidence: 99%

System dynamics model for intra-city multimodal transportation considering behavioral indicators and demand under uncertainty conditions

Tavakkolimoghaddam

Molana

Javadi

et al. 2022

JAMR

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PurposeBy designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.Design/methodology/approachThe paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.FindingsFour scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.Originality/valueThe value of this paper is considering uncertainty in traffic optimization; taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status; investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.

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“…( 2021 ), Thombre and Agarwal ( 2021 ), Truong and Truong ( 2021 ), Vo et al. ( 2021 ), Wang and Noland ( 2021 ), Wang et al. ( 2021b ), Zhang and Fricker ( 2021 ), Zhou et al.…”

Section: Review Of the Literaturementioning

confidence: 99%

“…( 2021b ), Teixeira and Lopes ( 2020 ), Truong ( 2021 ), Truong and Truong ( 2021 ),Vo et al. ( 2021 ), Vrabac et al. ( 2021 ), Wang and Noland ( 2021 ), Wang et al.…”

Section: Mobility/transportation Data Collecting Streams During Pande...mentioning

confidence: 99%

Data analytics during pandemics: a transportation and location planning perspective

2022

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The recent COVID-19 pandemic once again showed the value of harnessing reliable and timely data in fighting the disease. Obtained from multiple sources via different collection streams, an immense amount of data is processed to understand and predict the future state of the disease. Apart from predicting the spatio–temporal dynamics, it is used to foresee the changes in human mobility patterns and travel behaviors and understand the mobility and spread speed relationship. During this period, data-driven analytic approaches and Operations Research tools are widely used by scholars to prescribe emerging transportation and location planning problems to guide policy-makers in making effective decisions. In this study, we provide a review of studies which tackle transportation and location problems during the COVID-19 pandemic with a focus on data analytics. We discuss the major data collecting streams utilized during the pandemic era, highlight the importance of rapid and reliable data sharing, and give an overview of the challenges and limitations on the use of data.

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A mixed-equilibrium model of individual and household activity–travel choices in multimodal transportation networks

Cited by 8 publications

References 86 publications

Dynamics of Campus Travel Behavior under the COVID-19 Pandemic

Dynamics of Campus Travel Behavior under the COVID-19 Pandemic

System dynamics model for intra-city multimodal transportation considering behavioral indicators and demand under uncertainty conditions

Data analytics during pandemics: a transportation and location planning perspective

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