The datasets in this zip file are in support of Intelligent Transportation Systems Joint Program Office (ITS JPO) report FHWA-JPO-14-134, "Dynamic Mobility Applications Policy Analysis: Policy and Institutional Issues for Integrated Dynamic Transit Operations (IDTO)": https://rosap.ntl.bts.gov/view/dot/3553 The compressed zip file totals 0.6 GB in size. The zip file have been uploaded as-is; no further documentation was supplied by NTL, excepted as noted: All located .docx files were converted to .pdf document files which are an archival format. These pdfs were then added to the zip file alongside the original .docx files. The zip file can be unzipped using any zip compression/decompression software. This zip file contains files in the following formats: .pdf document files which can be read using any pdf reader; .cvs text files which can be read using any text editor; .docx document files which can be read in Microsoft Word and some other word processing programs; . xlsx spreadsheet files which can be read in Microsoft Excel and some other spreadsheet programs [software requirements]. These files were last accessed in 2017. To view the related publication see: https://rosap.ntl.bts.gov/view/dot/3553 Other related publications can also be found in the ITSJPO collection in ROSA P: https://rosap.ntl.bts.gov/cbrowse?pid=dot%3A239&parentId=dot%3A239

This table shows the number and percent of people in the contiguous United States (excludes Alaska and Hawaii) potentially exposed to different levels of noise from combined aviation, road and passenger rail sources.

Release Note

BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled.

Description

Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences.

Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.

This table shows the number and percent of people in the contiguous United States (excludes Alaska and Hawaii) potentially exposed to different levels of noise from passenger rail sources.