Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

Suryani, Erma; Hendrawan, Rully Agus; Adipraja, Philip Faster Eka; Wibisono, Arif; Widodo, Basuki; Indraswari, Rarasmaya

doi:10.1080/03081060.2020.1805543

Cited by 11 publications

(4 citation statements)

References 24 publications

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“…Khosravi et al (2020) Determine the most effective policies to respond to changing travel demand by combining system dynamics and data envelopment. Suryani, Hendrawan, Adipraja, et al (2020) To evaluate and improve the effectiveness of transportation systems and reduce traffic congestion. Xue et al (2020) Use system dynamics to analyze the benefits of transit metropolis construction.…”

Section: Author (Year) Analysismentioning

confidence: 99%

Linking integrity with road pricing cause-and-effect model: A system dynamics simulation approach

Mansur

Kamaruzzaman²,

Ahmarofi³

et al. 2023

JGI

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With Malaysia's rapid urbanisation and continuous improvement of living standards, vehicle ownership and trip volume continue to grow. Increases in motor traffic in large cities and their environs result in a number of social, environmental, and economic issues, which are frequently attributable to the widespread use of automobiles as the primary mode of urban transportation. This exacerbates traffic congestion on the country's highways, particularly in urban areas such as Kuala Lumpur. This traffic congestion poses an ongoing threat to the sustainability of transport development. Thus, by using the system dynamics, this study establishes a cause-and-effect relationship regarding the implementation of road pricing as a tool for reducing congestion and a stepping stone for enhancing sustainability. Road pricing is a direct charge assessed to drivers who use the road network with the goal of reducing the number of private vehicles on the road during peak hours. The developed Causal Loop Diagram (CLD) composed of five subsystems: road congestion, road attractiveness, new road construction, public transportation, and road pricing. The road congestion, new road construction, and road pricing all encounter mutual reinforcement as a result of a variety of negative polarities. As a result, authorities should place a greater emphasis on these loopholes, as they will inevitably result in unexpected changes. Additionally, by incorporating holistic perspectives from previous works and experts in the field, CLD can aid in identifying the primary factors underlying the problem being studied. In future work, the developed CLD should be extended to the next stage of the SD model, dubbed stock-flow-diagram (SFD).

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Section: Author (Year) Analysismentioning

confidence: 99%

Linking integrity with road pricing cause-and-effect model: A system dynamics simulation approach

Mansur

Kamaruzzaman²,

Ahmarofi³

et al. 2023

JGI

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“…In another study, Suryani et al (2020) evaluated the effectiveness of transportation systems in reducing traffic congestion through the use of simulation models and scenario development. An SD framework was used to test and evaluate the alternative future strategies for the city of Surabaya, Indonesia.…”

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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“…As of July 2020, researchers in [12] have identified a need for further investigation on modelling the transmission of COVID-19 through public transportation, and leveraging contact tracing to prevent the disease from spreading in an uncontrolled manner. Studies of public transportation networks focus on system infrastructure with higher emphasis on optimization of route efficiency by leaving room for future research on passenger activity [13] and capacity planning of the public transportation vehicles [14], as well as the use of autonomous robots to deliver several services [15]. In addition to these, research on the readiness / preparedness of public transportation systems against pandemics has become critical [16].…”

Section: Related Work and State Of The Artmentioning

confidence: 99%

Transit networks, social contacts and open data meet public transportation plans for post-COVID-19: A Canadian case study

Benning¹,

Calles²,

Kantarcı³

et al. 2021

Preprint

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This article presents a practical method for the assessment of the risk profiles of communities by tracking / acquiring, fusing and analyzing data from public transportation, district population distribution, passenger interactions and cross-locality travel data. The proposed framework fuses these data sources into a realistic simulation of a transit network for a given time span. By shedding credible insights into the impact of public transit on pandemic spread, the research findings will help to set the groundwork for tools that could provide pandemic response teams and municipalities with a robust framework for the evaluations of city districts most at risk, and how to adjust municipal services accordingly.

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Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

Cited by 11 publications

References 24 publications

Linking integrity with road pricing cause-and-effect model: A system dynamics simulation approach

Linking integrity with road pricing cause-and-effect model: A system dynamics simulation approach

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

Transit networks, social contacts and open data meet public transportation plans for post-COVID-19: A Canadian case study

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