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Development of a Roadside LiDAR-Based Situational Awareness System for Work Zone Safety: Proof-of-Concept Study [supporting dataset]

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  • Creators:
  • Corporate Creators:
  • Corporate Contributors:
  • Subject/TRT Terms:
  • Publication/ Report Number:
    TTI 05-03
  • DOI:
  • Resource Type:
    Dataset
  • Geographical Coverage:
    United States
  • Corporate Publisher:
    Safety through Disruption (Safe-D) University Transportation Center (UTC)
  • Abstract:
    Roadway construction and maintenance have become increasingly common as the U.S. transportation system ages and the population and traffic volume increase. This places more and more work zone workers near high-speed vehicles and increases the probability of being struck by them. This project innovatively deployed 360-degree LiDAR sensors at the roadside and tested their potential to provide work zone safety in terms of detection accuracy, efficiency, and ease of use. Researchers developed a set of algorithms to collect and interpret real-time information for each approaching vehicle and worker (e.g., location, speed, and direction) in and outside work zones using roadside LiDAR. Ultimately, the outcome of this pilot study could lead to developing a full-scale warning system deployable in a real work zone environment. Such a system could detect and analyze live traffic and work zone activity, activate the appropriate warning scheme, and deliver information to roadway workers in work zones in a timely manner so they can take evasive actions instead of relying on traditional “passive” safety countermeasures. This kind of panoramic, trajectory-level data for work zone actors can be used to develop a next-generation work zone situational awareness system.

    The total size of the zip file is 6.1 GB. The .csv, Comma Separated Value, file is a simple format that is designed for a database table and supported by many applications. The .csv file is often used for moving tabular data between two different computer programs, due to its open format. The most common software used to open .csv files are Microsoft Excel and RecordEditor, (for more information on .csv files and software, please visit https://www.file-extensions.org/csv-file-extension). The .pdf file format is an Adobe Acrobat Portable Document Format (PDF) file and can be opened with the Adobe Acrobat software. The .txt file type is a common text file, which can be opened with a basic text editor. The most common software used to open .txt files are Microsoft Windows Notepad, Sublime Text, Atom, and TextEdit (for more information on .txt files and software, please visit https://www.file-extensions.org/txt-file-extension). The file extension .png is commonly used for images in Portable Network Graphics file format. PNG is a bitmap graphics format similar to GIF, that uses image compression mainly for web purposes (for more information on .png files and software, please visit https://www.file-extensions.org/png-file-extension). The .bag files are only usable with the program MATLAB. Please contact your institution to obtain a copy of MATLAB or use their free trial to access these files.

  • 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. The current level of dataset documentation is the responsibility of the dataset creator. 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.8083359). NTL staff last accessed this dataset at its repository URL on 2024-02-02. 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.
  • Format:
    ZIP
  • Funding:
    69A3551747115
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:594c1084d3a2c60bfdcde322d7d51c2a42ad93ce8cc99d8c7ba5761a307c0da910571482c12e63c2083fedef0d85ae15863690f351a131b293f9c412a8a7ff54
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  • File Type:
    Filetype[JSON - 3.14 KB ]

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