The statistic shows estimated internet data traffic per month in the United States from 2018 to 2023. In 2018, total internet data traffic was estimated to amount to 33.45 million exabytes per month.

The FDOT Annual Average Daily Traffic feature class provides spatial information on Annual Average Daily Traffic section breaks for the state of Florida. In addition, it provides affiliated traffic information like KFCTR, DFCTR and TFCTR among others. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 06/14/2025.Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/aadt.zip

Feature layer containing authoritative traffic count points for Sioux Falls, South Dakota.The traffic counts listed are 24-hour, weekday, two-directional counts. Traffic counts are normally collected during the summer months, but may be taken any season, as weather permits. The traffic counts are factored by the day of the week as well as by the month of the year to become an Average Annual Daily Total (AADT). Traffic volumes (i.e. count data) can fluctuate depending on the month, week, day of collection; the weather, type of road surface, nearby construction, etc. All of the historical data should be averaged to reflect the "normal" traffic count. More specific count data (time, date, hourly volume) can be obtained from the Sioux Falls Engineering Division at 367-8601.

Linear network representing the estimated traffic flows for roads and highways managed by the Ministry of Transport and Sustainable Mobility (MTMD). These flows are obtained using a statistical estimation method applied to data from more than 4,500 collection sites spread over the main roads of Quebec. It includes DJMA (annual average daily flow), DJME (summer average daily flow), DJME (summer average daily flow (June, July, August, September) and DJMH (average daily winter flow (December, January, February, March) as well as other traffic data. It is important to note that these values are calculated for total traffic directions. Interactive map: Some files are accessible by querying a section of traffic à la carte with a click (the file links are displayed in the descriptive table that is displayed when clicking): • Historical aggregated data (PDF) • Annual reports for permanent sites (PDF and Excel) • Hourly data (hourly average per weekday per month) (Excel) • Annual reports for permanent sites (PDF and Excel) • Hourly data (hourly average per weekday per month) (Excel)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Cars.com is a U.S.- based automotive classifieds website which recorded nearly 22 million average monthly unique visitors from the start of 2019 to June 30th, 2019. In the same period of 2023, average monthly unique visitors to the site raised to 27.7 million.

Traffic data for key Brisbane City Council managed roads. Includes monthly traffic volume, travel time and speed.

The data which was received as Incomplete and Incorrect was marked as NA in the report.

Information on Traffic Management is available on the Brisbane City Council website.

This data was previously published in a different format in the following two datasets:

Traffic Management — Key Corridor — Average Peak Travel timesTraffic Management — Key Corridor — Performance Report.

The Data and resources section of this dataset contains further information for this dataset.

In 2024, smartphones across the globe used an average of 20.29 gigabytes of mobile data per month, up from 17.27 gigabytes the previous year. This figure is expected to reach 23.78 gigabytes in 2025, and 42.38 gigabytes by 2029.

Feature layer containing authoritative traffic count points for the traffic model for Sioux Falls, South Dakota. The data in the traffic counts model feature layer is collected for traffic count modeling and transportation planning. This data is collected on a five-to-seven-year basis, with data from 2001, 2008, 2013, 2018, and 2023. The traffic counts are 24-hour, weekday, two-directional counts. Traffic counts are normally collected during the summer months, but may be taken any season, as weather permits. The traffic counts are factored by the day of the week as well as by the month of the year to become an Average Annual Daily Total (AADT). Traffic volumes (i.e., count data) can fluctuate depending on the month, week, day of collection, the weather, type of road surface, nearby construction, etc. All the historical data should be averaged to reflect the "normal" traffic count. More specific count data (time, date, hourly volume) can be obtained from the Sioux Falls Engineering Division at 605-367-8601.

This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. For a more detailed description, please go to https://tas.chicago.gov, click the About button at the bottom of the page, and then the MAP LAYERS tab.

The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (nonfreeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every ten minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimate by traffic segments gives the observed speed typically for one-half mile of a street in one direction of traffic.

Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

This is a dynamic traffic map service with capabilities for visualizing traffic speeds relative to free-flow speeds as well as traffic incidents which can be visualized and identified. The traffic data is updated every five minutes. Traffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%Esri's historical, live, and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. Historical traffic is based on the average of observed speeds over the past three years. The live and predictive traffic data is updated every five minutes through traffic feeds. The color coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation and field operations. The traffic map layer contains two sublayers: Traffic and Live Traffic. The Traffic sublayer (shown by default) leverages historical, live and predictive traffic data; while the Live Traffic sublayer is calculated from just the live and predictive traffic data only. A color coded traffic map image can be requested for the current time and any time in the future. A map image for a future request might be used for planning purposes. The map layer also includes dynamic traffic incidents showing the location of accidents, construction, closures and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis. The service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. In the coverage map, the countries color coded in dark green support visualizing live traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, including a data coverage map, visit the directions and routing documentation and ArcGIS Help.

The PTV traffic volume API provides traffic volumes for various time periods and vehicle segments for a specific location (x,y coordinate) and a buffer around the location in Germany and France.

All traffic volumes are available for the following vehicle segments: - Cars Trucks up to 3.5t - Trucks between 3.5 and 7.5t - Trucks between 7.5 and 12t - Trucks above 12t

Time periods for Germany are: - Average Daily Traffic for Monday - Average Daily Traffic for Tuesday/Wednesday/Thursday - Average Daily Traffic for Friday - Average Daily Traffic for Saturday - Average Daily Traffic for Sunday

Time periods for France are: - Average Annual Daily Traffic (AADT) - Truck ratio - January Monthly Average Daily Traffic (Jan- MADT) - February - Monthly Average Daily Traffic (Feb-MADT) - .... - December - Monthly Average Daily Traffic (Dec-MADT) 

This dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), NYCT bus, MTA Bus, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, Bridges and Tunnels and Staten Island Railway on a monthly basis.

Traffic Volume Trends is a monthly report based on hourly traffic count data reported by the States. These data are collected at approximately 5,000 continuous traffic counting locations nationwide and are used to estimate the percent change in traffic for the current month compared with the same month in the previous year. Estimates are re-adjusted annually to match the vehicle miles of travel from the Highway Performance Monitoring System and are continually updated with additional data.

Urban SDK is a GIS data management platform and global provider of mobility, urban characteristics, and alt datasets. Urban SDK Traffic data provides traffic volume, average speed, average travel time and congestion for logistics, transportation planning, traffic monitoring, routing and urban planning. Traffic data is generated from cars, trucks and mobile devices for major road networks in US and Canada.

"With the old data I used, it took me 3-4 weeks to create a presentation. I will be able to do 3-4x the work with your Urban SDK traffic data."

Traffic Volume, Speed and Congestion Data Type Profile:

• Traffic volume in annual average daily and daily traffic volumes per roadway
• Average travel speed in 15 minute and hourly intervals per roadway
• Travel time in seconds in 15 minute intervals per roadway
• Commute travel time in minutes in annual interval estimates in geohash boundaries
• Congested roadway segments based on travel time reliability in monthly intervals per roadway
• Traffic data attributed spatially to state, county, road functional class, road name, road segment, segment length in km or miles as geojson

Industry Solutions include:

• Transportation Planning
• Traffic Monitoring
• Congestion Management and Trend Analysis
• Travel Demand Modeling
• Traffic Impact Analysis
• Parking Analysis
• Transit System Planning
• Route Planning
• Civil Engineering
• Site Selection

Use cases:

• Traffic monitoring, data analysis, and forecasting for transportation, transit, and urban planning.
• Improve dynamic routing with accurate travel time and congestion data
• Environmental and emissions analysis
• Travel demand and transportation modeling
• Location analysis and assessment for commercial site selection for retail or logistics related locations

Monthly traffic volume statistics from Permanent counters for the period January 2011 to June 2011. This includes Monthly Average Daily Traffic (MADT), Monthly Average Weekday Traffic, Monthly Average Weekend Traffic, and Monthly Average Daily Traffic by Length bin using the BC 5-bin scheme.

Analysis of ‘Annual Average Daily Traffic (AADT) Volumes’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/352f50a3-9644-4887-b7a9-c7cf0d86b614 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Traffic Volumes (a.k.a.Traffic Counts) are surveyed from the California State Highway System. The data originated from Caltrans Traffic Census database compiled by Caltrans Districts Offices. The Districts calculated the volumes hourly, daily, and monthly to derive an annual average daily traffic count. Volumes are surveyed in both directions, "Back" describes south or west of the location at which the count was recorded and "Ahead" describes north or east of the location at which the count was recorded. More info: https://dot.ca.gov/programs/traffic-operations/census

--- Original source retains full ownership of the source dataset ---

The monthly data traffic in North America is projected to amount to 1.88 exabytes (EB) by 2029. In 2024, the average data traffic amounted to almost 0.68 EB per month.

Google.com recorded an average monthly traffic of 4.79 billion visits in Japan from September to November 2024, which made it the most visited website. It was followed by Yahoo.co.jp and Youtube.com.

India Freight Traffic: Average Lead: Container Service data was reported at 885.000 km in Nov 2018. This records a decrease from the previous number of 897.000 km for Oct 2018. India Freight Traffic: Average Lead: Container Service data is updated monthly, averaging 1,105.000 km from Apr 2009 (Median) to Nov 2018, with 115 observations. The data reached an all-time high of 1,312.000 km in May 2009 and a record low of 854.000 km in Jul 2018. India Freight Traffic: Average Lead: Container Service data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB001: Railway Statistics: Passenger and Freight Traffic: Monthly.