Advanced tutorial on microscopic discrete-event traffic simulation

Miller, John A.; Peng, Hao; Bowman, Casey N.

doi:10.1109/wsc.2017.8247826

Cited by 3 publications

(3 citation statements)

References 76 publications

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“…Article [29] with 190 citations is at the second position in the top 10 highly cited articles. This article introduces two models based on Kalman filter theory for short-term traffic volume forecasting and is regarded as the first one to use Kalman filter for traffic volume forecasting [30]. Since then, a large number of Kalman-filtering-based methods with some variants are proposed for traffic forecasting, and the article [29] receives much attention and high citations.…”

Section: Analysis Of Highly Cited Articlesmentioning

confidence: 99%

A scientometric review of research on traffic forecasting in transportation

Liu

Qiao

et al. 2020

IET Intelligent Trans Sys

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Research on traffic forecasting in transportation has received worldwide concern over the past three decades. While there are comprehensive review studies on traffic forecasting, few of them explore the research advancement in this field from a visual perspective. With the help of CiteSpace and VOSviewer, this study uses scientometric review to identify the evolution and emerging trends of the research in the field. Totally, 1536 bibliographic records with references are extracted from Web of Science and used as the datasets to form the author network, institutional network, keyword network, and co‐citation network. The visualization of the results characterizes the research progress in the field. It can be found that Eleni I. Vlahogianni receives the highest citation frequency, China and the United States contribute most of the journal articles. Some influential institutions and articles are also identified. With the author keyword network, the words “recurrent neural network”, “convolutional neural network”, “spatio‐temporal correlation”, “traffic pattern”, and “feature selection” are identified as the emerging trends. Also, the document citation bursts reveal that the applications of combined models and the study of traffic flow forecasting in atypical situations are becoming the emerging trends. This study provides a valuable reference for the research community in this field.

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Section: Analysis Of Highly Cited Articlesmentioning

confidence: 99%

A scientometric review of research on traffic forecasting in transportation

Liu

Qiao

et al. 2020

IET Intelligent Trans Sys

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“…Paper presented by Miller et al [15] reviews the features and challenges of microscopic simulations. The paper describes conventional techniques used in simulations like CA, event simulations, machine learning and regression.…”

Section: Survey Of Reviews On Traffic Flow Simulationsmentioning

confidence: 99%

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Rydzewski¹,

Czarnul²

2020

IET intell. transp. syst

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Over the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which are of the greatest value to city citizens. In this work, the authors expose various problems within this area having reviewed and analysed over 130 papers selected out of 1200 works in the field of urban simulations. The study describes the selection process of important papers and highlights characteristics of microsimulations, macrosimulations, computation optimisations and other approaches found in the literature which are especially useful and should be further built on in the future. They present and compare results provided in reviewed works in terms of throughput improvement, queue, waiting and travel time reduction, vehicle speed increase, speed‐ups as well as assumed simulation parameters. Finally, they focus on research gaps, such as a small number of works considering crisis simulations, few real‐world scale simulations as well as on software architectural changes and low‐level optimizations.

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“…Research carried out by Miller et al [14] has highlighted the variety of models required for an accurate traffic simulator. There are two main types of model required, a traffic model and a driver behavior model.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling a Smart Motorway

Richardson¹,

Davies

Newell

2019

Advances in Intelligent Systems and Computing

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The increasing number of vehicles in the UK is putting high levels of strain upon the motorway's infrastructure. Smart Motorways have been implemented in the UK using smart technology to try and reduce congestion. To test systems before they are physically built they are simulated using objects models and GIS data. This paper has modelled a new smart traffic light system for a slip road joining a smart motorway. The smart traffic light models have been simulated alongside Driver Behavior models. The driver behavior models have been designed to validate that the smart traffic light system can adapt to continuously fluctuating traffic flow. The smart traffic light system has been successfully validated and reduced the number of congestion alerts by 80% on the smart motorway.

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Advanced tutorial on microscopic discrete-event traffic simulation

Cited by 3 publications

References 76 publications

A scientometric review of research on traffic forecasting in transportation

A scientometric review of research on traffic forecasting in transportation

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Modelling a Smart Motorway

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