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v1.1 update README
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4 changes: 2 additions & 2 deletions Getting traffic safety data from online resource.Rmd
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ClusterR, RColorBrewer, rmdformats, ggcal, gtools)
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In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript **Bridging the Gap between Transportation Safety Research and its Incorporation inOptimization Models: a Detailed Review and Perspective**. It has been submitted to _[Transportation Research Part C: Emerging Technologies](https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies)_.
In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript **Bridging the Gap between Transportation Safety Research and its Incorporation in Optimization Models: a Detailed Review and Perspective**. It has been submitted to _[Transportation Research Part C: Emerging Technologies](https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies)_.

This vignette includes examples on the following five aspects:

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3. **An example of clustering**
4. **Statistical methods**: logistic regression and Poisson regression

To maximize the readability of this vignette, we hided all R codes by default, but readers can look into any code by clicking the `code` button.
To maximize the readability of this website, we hided all R codes by default, but readers can look into any code by clicking the `code` button. The data folder is not uploaded to the GitHub repository since the files exceed the limited size, but all the data are open access and interested readers can download all the files at the link given in each section.



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4 changes: 2 additions & 2 deletions Getting_traffic_safety_data_from_online_resource.html
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<p>In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript <strong>Bridging the Gap between Transportation Safety Research and its Incorporation inOptimization Models: a Detailed Review and Perspective</strong>. It has been submitted to <em><a href="https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies">Transportation Research Part C: Emerging Technologies</a></em>.</p>
<p>In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript <strong>Bridging the Gap between Transportation Safety Research and its Incorporation in Optimization Models: a Detailed Review and Perspective</strong>. It has been submitted to <em><a href="https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies">Transportation Research Part C: Emerging Technologies</a></em>.</p>
<p>This vignette includes examples on the following five aspects:</p>
<ol style="list-style-type: decimal">
<li><strong>Bibliographic analysis</strong>: Bibliometric Summary for Transportation Safety, Bibliographic Network Matrices - Journal Names, keyword co-occurrences network, a Conceptual Structure Map</li>
<li><strong>Extracting online transportation safety data</strong>: Crash-related data, traffic flow data, and weather data.</li>
<li><strong>An example of clustering</strong></li>
<li><strong>Statistical methods</strong>: logistic regression and Poisson regression</li>
</ol>
<p>To maximize the readability of this vignette, we hided all R codes by default, but readers can look into any code by clicking the <code>code</code> button.</p>
<p>To maximize the readability of this website, we hided all R codes by default, but readers can look into any code by clicking the <code>code</code> button. The data folder is not uploaded to the GitHub repository since the files exceed the limited size, but all the data are open access and interested readers can download all the files at the link given in each section.</p>
<div id="bibliographic-analysis" class="section level1 tabset tabset-fade">
<h1><span class="header-section-number">1</span> Bibliographic analysis</h1>
<hr />
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10 changes: 8 additions & 2 deletions README.md
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# TrafficSafetyReviewRmarkdown
# Supplementary materials for transportation safety review

This is a repository for obtaining traffic safety data from online resources as described in the NSF project.
This repository serves as the supplementary materials to create reproducible examples in the manuscript:

> Bridging the Gap between Transportation Safety Research and its Incorporation in Optimization Models: a Detailed Review and Perspective.
It has been submitted to _[Transportation Research Part C: Emerging Technologies](https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies)_.

You can preview a website generated by this repository at: [https://caimiao0714.github.io/TrafficSafetyReviewRmarkdown/](https://caimiao0714.github.io/TrafficSafetyReviewRmarkdown/). The website is maintained by [Miao Cai](https://github.com/caimiao0714). You can contact him by Email: [[email protected]](mailto:[email protected]).

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