Intra-City Traffic Data Visualization: A Systematic Literature Review

Clarinval, Antoine; Dumas, Bruno

doi:10.1109/tits.2021.3092036

Cited by 7 publications

(2 citation statements)

References 195 publications

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“…Commonly used visualization techniques include line charts, bar charts, heatmaps, histograms, and geospatial maps. Geospatial maps represent the most commonly employed method for visualizing traffic data, and 2D visualization is more commonly used in the literature than its 3D counterpart [23].…”

Section: Visualization Techniquesmentioning

confidence: 99%

Predictive Analyses of Traffic Level in the City of Barcelona: From ARIMA to eXtreme Gradient Boosting

Garcia,

Calvet,

Carracedo

et al. 2024

Applied Sciences

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This study delves into the intricate dynamics of urban mobility, a pivotal aspect for policymakers, businesses, and communities alike. By deciphering patterns of movement within a city, stakeholders can craft targeted interventions to mitigate traffic congestion peaks, optimizing both resource allocation and individual travel routes. Focused on Barcelona, Spain, this paper draws on data sourced from the city council’s open data service. Through a blend of exploratory analysis, visualization techniques, and modeling methodologies—including time series analysis and the eXtreme Gradient Boosting (XGBoost) algorithm—the research endeavors to forecast traffic conditions. Additionally, a study of variable importance is carried out, and Shapley Additive Explanations are applied to enhance the interpretability of model outputs. Findings underscore the limitations of traditional forecasting methods in capturing the nuanced spatial and temporal dependencies present in traffic flows, particularly over medium- to long-term horizons. However, the XGBoost model demonstrates robust performance, with the area under ROC curves consistently exceeding 80%, indicating its efficacy in handling non-linear traffic data variables.

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Section: Visualization Techniquesmentioning

confidence: 99%

Predictive Analyses of Traffic Level in the City of Barcelona: From ARIMA to eXtreme Gradient Boosting

Garcia,

Calvet,

Carracedo

et al. 2024

Applied Sciences

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“…Our contributions are summarized as follows: We first establish a common characterization that allows us to organize contributions from a multitude of domains, including visualization, architecture, engineering, and urban planning. We introduce a comprehensive survey on 3D urban visual analytics. Inspired by other surveys [DFT19, PSS*21, CD21], we follow a human‐centered, interrogative method in which we classify each evaluated work with respect to Munzner's [Mun15] analytical framework of Why is 3D urban data being analyzed, What data is being analyzed , and How it is being analyzed and visualized . We report a series of research directions and open problems in 3D urban visual analytics. These include visual metaphors, navigation & occlusion, data and systems integration, evaluation of visual designs, and guided explorations. …”

Section: Introductionmentioning

confidence: 99%

The State of the Art in Visual Analytics for 3D Urban Data

Miranda,

Ortner,

Moreira

et al. 2024

Computer Graphics Forum

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Urbanization has amplified the importance of three‐dimensional structures in urban environments for a wide range of phenomena that are of significant interest to diverse stakeholders. With the growing availability of 3D urban data, numerous studies have focused on developing visual analysis techniques tailored to the unique characteristics of urban environments. However, incorporating the third dimension into visual analytics introduces additional challenges in designing effective visual tools to tackle urban data's diverse complexities. In this paper, we present a survey on visual analytics of 3D urban data. Our work characterizes published works along three main dimensions (why, what, and how), considering use cases, analysis tasks, data, visualizations, and interactions. We provide a fine‐grained categorization of published works from visualization journals and conferences, as well as from a myriad of urban domains, including urban planning, architecture, and engineering. By incorporating perspectives from both urban and visualization experts, we identify literature gaps, motivate visualization researchers to understand challenges and opportunities, and indicate future research directions.

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Daten vor Ort erleben: Eine Fallstudie zur Visualisierung der Luftqualität für Bürgerinnen und Bürger

Huber

Nagel

Stuckenschmidt

2023

KN J. Cartogr. Geogr. Inf.

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Visualizing urban data has different purposes. Besides more traditional goals such as supporting experts to decide on smart city policies, supporting citizens to understand aspects of the city relevant to one’s everyday life needs different visualization approaches. In contrast to urban dashboards, which typically show various data sources in a more or less unified way, visualizations tailored for one specific task may be more appropriate for citizens. This paper introduces data experience points where people can experience data on location on their own device, and explore and understand urban phenomena through visualizations. Based on an expert workshop, we propose a set of design goals for these data experience points, and demonstrate the concept through a case study of visualizing air quality data. We designed and implemented multiple prototypes in this case study, and gathered feedback at a public outreach event.

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Intra-City Traffic Data Visualization: A Systematic Literature Review

Cited by 7 publications

References 195 publications

Predictive Analyses of Traffic Level in the City of Barcelona: From ARIMA to eXtreme Gradient Boosting

Predictive Analyses of Traffic Level in the City of Barcelona: From ARIMA to eXtreme Gradient Boosting

The State of the Art in Visual Analytics for 3D Urban Data

Daten vor Ort erleben: Eine Fallstudie zur Visualisierung der Luftqualität für Bürgerinnen und Bürger

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