Details:

Creators:
Sullivan, James ; Sentoff, Karen
Sullivan, James ; Sentoff, Karen Less -
Corporate Creators:
University of Vermont. Transportation Research Center
Corporate Contributors:
United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
[+]
Data Files Emissions Testing Exhaust Gases Highway Traffic Control Systems Horizontal Curvature Hybrid Electric Vehicles Hybrid Vehicles Internal Combustion Engines Intersection Control K-S Test Road Grade Second-by-second Emissions Signalized Intersections Speed
Publication/ Report Number:
NCST-UVM-RR-19-05
DOI:
https://doi.org/10.15146/R36975
Resource Type:
Dataset
Geographical Coverage:
United States
Corporate Publisher:
National Center for Sustainable Transportation (NCST) (UTC)
Abstract:
In this study, a second-by-second (SbS) data set obtained from monitoring vehicle emissions over a series of 75 test runs from 2 test vehicles (a conventional vehicle (CV) and a hybrid-electric vehicle (HEV)) over an 18-month period in 2010-2011 during real-world on-road operations on a specified 32-mile route in Chittenden County, Vermont was used in an innovative new method of analysis to assess emissions differences between the two propulsion systems and attribute these differences to physical roadway/infrastructure characteristics. The K-S test was used to assess the difference between the cumulative distributions of the CV and HEV emissions samples on each link, and the K-S test statistic was regressed against the full set of roadway link characteristics. The regression results allowed the team to identify specific roadway characteristics that contribute to emissions differences between the vehicle types. Overall, the models that included maximum grade and intersection control type performed best, however speed limit and horizontal curvature were also shown to be important. The performance differences identified in this project confirm that engine controls that are responsive to roadway characteristics are necessary.

The total size of the described zip file is 8.5MB. The ZIP file for this dataset contains files with the following files extensions: 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). File extension .md is used in creating GitHub Issues, and can be opened in a basic text editor. Files with the extension .PNG are image files that can be opened with any basic photo viewer or editor. 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. Any text editor or spreadsheet program will open .csv files. PDF are used to display text and images and can be opened with any PDF reader or editor. Files with the .xlsx extension are Microsoft Excel spreadsheet files. These can be opened in Excel or open source spreadsheet programs. .py files are written in the Python programming language, and can be opened in basic text editors or in Python programming environments. Reading Python files will take special knowledge of programming. Files with the extension .bat traditionally used for batch files. A batch file is a text file that contains a sequence of commands for a computer operating system. These can be opened in an editor or in command line. This will take special knowledge or appropriate software to operate.


Content Notes:
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. NTL staff last accessed this dataset at https://datadryad.org/stash/dataset/doi:10.15146/R36975 on 2022-09-29. 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:
USDOT Grant 69A3551747114
Collection(s):
US Transportation Collection
Main Document Checksum:
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urn:sha256:56868aa4cf2f836a72ba415711a3d7cd15167a17db44d46ac8ce9ff7fe9b9aae
Download URL:
https://rosap.ntl.bts.gov/view/dot/64429/dot_64429_DS1.json
File Type:

Supporting Files

• R36975

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