United States Department of Transportation
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Enhancing Collaboration Through Web-Based Visualization and Analysis of Traffic Crash Data [supporting dataset]
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2024-10-01
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[JSON-7.09 KB]
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Abstract:It is widely accepted that road traffic safety is a significant public health issue. One of the effective ways to improve road traffic safety is analyzing crash data to understand where traffic accidents occur, identify associated spatial and temporal patterns, and determine causation. In the State of New Mexico, locations of traffic accidents are currently visualized using a variety of static maps. Although these statics maps are easier to create and producers can control how users view the data, they are not able to visualize crash density information because users cannot zoom in or zoom out, and hence cannot identify any associated spatial and temporal patterns. To solve the problems inherent with the current static maps, this research project focused on exploring the utility of dynamic and interactive web mapping and visualization techniques to visualize and analyze traffic crash data with the aim of helping transportation professionals determine the causes of traffic crashes and identify high-crash locations and other associated spatial and temporal patterns, and ultimately, achieving improved safety, enhanced resiliency, and increased efficiency for road users. This was achieved exclusively with open source tools and the implementation of well-known geospatial statistical analysis tools proven effective in traffic safety analysis.
The total size of the zip file is 27.6 KB. The .py file extension is commonly used for files containing source code written in Python programming language. Python is a dynamic object-oriented programming language that can be used for many kinds of software development (for more information on .py files and software, please visit https://www.file-extensions.org/py-file-extension). File extension .gitignore is associated with Git, a version control system developed by Linus Torvalds for various platforms that can run on local machine also as server app. These .gitignore files are text configuration files used by Git used to determine which files and directories to ignore, before user make a commit (for more information on .gitignore files and software, please visit https://www.file-extensions.org/gitignore-file-extension). The file extension .md is among others related to texts and source codes in Markdown markup language. Markdown is a lightweight markup language, to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML) (for more information on .md files and software, please visit https://www.file-extensions.org/md-file-extension). The .toml file type is a basic config, markup file. It is typically created in python environments such as the Python Package Index (for more information on .toml files and software, please visit https://www.file-extensions.org/toml-file-extension).
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Content Notes:National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. This dataset has been curated to CoreTrustSeal's curation level "C. Initial Curation." To find out more information on CoreTrustSeal's curation levels, please consult their "Curation & Preservation Levels" CoreTrustSeal Discussion Paper" (https://doi.org/10.5281/zenodo.11476980). NTL staff last accessed this dataset at its repository URL on 2024-10-21. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
Public Access Note: This item is made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Use the following citation:
Center for Pedestrian and Bicyclist Safety. (2024). Source code for CPBS Report 23UNM03 - Enhancing Collaboration through Web-based Visualization and Analysis of Traffic Crash Data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13870228
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