Visualization in Transportation: Challenges and Opportunities for Everyone

Pack, Michael L.

doi:10.1109/mcg.2010.79

Cited by 26 publications

(9 citation statements)

References 2 publications

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“…Demographic data about the inhabitants and quantitative measurable parameters include, among others, noise, sound barriers, air pollution, meteorological and microclimatic conditions, energy consumption, water and waste flows, traffic and the environment, traffic speed and accessibility to public transportation (i.e . Pack, 2010; Pelzer and Geertman, 2013; Stahre Wästberg et al., 2013; Wang and Li, 2010). There are also examples of visualization platforms that include social parameters , i.e.…”

Section: Results From the Literature Search: Answers To The Five Guidmentioning

confidence: 99%

In search of visualization challenges: The development and implementation of visualization tools for supporting dialogue in urban planning processes

Billger

Thuvander

Wästberg

2016

Environment and Planning B: Urban Analytics and City Science

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Today, urban planning processes involve many stakeholders and efficient dialogue tools are needed to support communication in transdisciplinary environments. The aim of our study is to identify visualization challenges in urban planning. Based on a state of the art study and a thematic analysis of 114 articles, published in 2004–2014 and found through snowball sampling, the development and implementation of digital visualization tools for dialogue are discussed. A wide range of examples of visualization tools for dialogue has been found; either based on 2D maps, 3D environments or gaming. The initiators of the development originate from different disciplines, such as geographic information (GI) science, computer graphics, 3D modelling, Virtual Reality, interaction design and urban planning. There has been an increasing amount of usability studies during recent years. There is a tendency for the usability studies to have gone from experimental and prototype studies to more and more concern real planning processes and implementation. Studies of implemented tools in real planning processes are, however, still rare. Gaming appears more and more frequently. Challenges are related to integration of qualitative and quantitative data, representation of data as regard appropriate levels of realism and detailing, as well as the user’s experience and the appearance of the digital models. There is a need to consider how we can achieve the full potential of visualization tools, including optimal effectiveness of visualization tools and processes for dialogue as well as how they can be implemented. Organizational preparedness is necessary, including clear ownership, allocation of resources for maintenance, competence and access to tools and technology.

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Section: Results From the Literature Search: Answers To The Five Guidmentioning

confidence: 99%

In search of visualization challenges: The development and implementation of visualization tools for supporting dialogue in urban planning processes

Billger

Thuvander

Wästberg

2016

Environment and Planning B: Urban Analytics and City Science

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“…On the lower end of the spectrum, Parallel coordinates plots (PCP) and trellis (small multiples of bar charts or scatter plots) are commonly used fast plotting tools and require less data preprocessing. For example, PCP can be applied to visualize the correlation/interaction among several crash descriptors including: cars involved, day/month effects, incident type, and road condition [45,53,55]. Additionally, the trellis plot was used by Cottrill and Thakuriah [54] to visualize variations in the number of crashes by different census tracts.…”

Section: Visualization Of High-dimensional Datasetsmentioning

confidence: 99%

A Review of Data Analytic Applications in Road Traffic Safety. Part 1: Descriptive and Predictive Modeling

Mehdizadeh

Cai

et al. 2020

Sensors

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This part of the review aims to reduce the start-up burden of data collection and descriptive analytics for statistical modeling and route optimization of risk associated with motor vehicles. From a data-driven bibliometric analysis, we show that the literature is divided into two disparate research streams: (a) predictive or explanatory models that attempt to understand and quantify crash risk based on different driving conditions, and (b) optimization techniques that focus on minimizing crash risk through route/path-selection and rest-break scheduling. Translation of research outcomes between these two streams is limited. To overcome this issue, we present publicly available high-quality data sources (different study designs, outcome variables, and predictor variables) and descriptive analytic techniques (data summarization, visualization, and dimension reduction) that can be used to achieve safer-routing and provide code to facilitate data collection/exploration by practitioners/researchers. Then, we review the statistical and machine learning models used for crash risk modeling. We show that (near) real-time crash risk is rarely considered, which might explain why the optimization models (reviewed in Part 2) have not capitalized on the research outcomes from the first stream.

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“…Outside the simulation realm, visualization applications can be found in virtual reality [16,17], safety [18,19], and transportation [20,21].…”

Section: Visualization In Constructionmentioning

confidence: 99%

A Framework for Visualizing Heterogeneous Construction Data Using Semantic Web Standards

Ali

Mohamed

2018

Advances in Civil Engineering

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3D Visualization provides a mean for communicating different construction activities to diverse audiences. e scope, level of detail, and time resolution of the 3D visualization process are determined based on the targeted audiences. Developing the 3D visualization requires obtaining and merging heterogeneous data from different sources (such as BIM model and CPM schedule). e data merging process is usually carried out on ad hoc basis for a specific visualization case which limits the reusability of the process. is paper discusses a framework for automatic merging of heterogeneous data to create a visualization. e paper describes developing an ontology which captures concepts related to the visualization process. en, heterogeneous data sources that are commonly used in construction are fed into the ontology which can be queried to produce different visualization scenarios. e potential of this approach has been demonstrated by providing multiple visualization scenarios that cover different audiences, levels of detail, and time resolutions.

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Visualization in Transportation: Challenges and Opportunities for Everyone

Cited by 26 publications

References 2 publications

In search of visualization challenges: The development and implementation of visualization tools for supporting dialogue in urban planning processes

In search of visualization challenges: The development and implementation of visualization tools for supporting dialogue in urban planning processes

A Review of Data Analytic Applications in Road Traffic Safety. Part 1: Descriptive and Predictive Modeling

A Framework for Visualizing Heterogeneous Construction Data Using Semantic Web Standards

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