This dataset consists of 24-hour traffic volumes which are collected by the City of Tempe high (arterial) and low (collector) volume streets. Data located in the tabular section shares with its users total volume of vehicles passing through the intersection selected along with the direction of flow.Historical data from this feature layer extends from 2016 to present day.Contact: Sue TaaffeContact E-Mail: sue_taaffe@tempe.govContact Phone: 480-350-8663Link to embedded web map:http://www.tempe.gov/city-hall/public-works/transportation/traffic-countsLink to site containing historical traffic counts by node: https://gis.tempe.gov/trafficcounts/Folders/Data Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changesPublish Method: AutomaticData Dictionary

This traffic-count data is provided by the City of Pittsburgh's Department of Mobility & Infrastructure (DOMI). Counters were deployed as part of traffic studies, including intersection studies, and studies covering where or whether to install speed humps. In some cases, data may have been collected by the Southwestern Pennsylvania Commission (SPC) or BikePGH.

Data is currently available for only the most-recent count at each location.

Traffic count data is important to the process for deciding where to install speed humps. According to DOMI, they may only be legally installed on streets where traffic counts fall below a minimum threshhold. Residents can request an evaluation of their street as part of DOMI's Neighborhood Traffic Calming Program. The City has also shared data on the impact of the Neighborhood Traffic Calming Program in reducing speeds.

Different studies may collect different data. Speed hump studies capture counts and speeds. SPC and BikePGH conduct counts of cyclists. Intersection studies included in this dataset may not include traffic counts, but reports of individual studies may be requested from the City. Despite the lack of count data, intersection studies are included to facilitate data requests.

Data captured by different types of counting devices are included in this data. StatTrak counters are in use by the City, and capture data on counts and speeds. More information about these devices may be found on the company's website. Data includes traffic counts and average speeds, and may also include separate counts of bicycles.

Tubes are deployed by both SPC and BikePGH and used to count cyclists. SPC may also deploy video counters to collect data.

NOTE: The data in this dataset has not updated since 2021 because of a broken data feed. We're working to fix it.

The American motor vehicle fleet traveled about 237.4 billion vehicle-miles in February 2025. Compared with January 2025, traffic decreased by about 13.7 billion vehicle-miles. Between January and December 2024, traffic volume came to around 3.3 trillion vehicle-miles of travel.

Point layer used to represent the spatial location of all Traffic Count Stations maintained and counted on an annual basis by Miami-Dade County Public Works and Waste Management Department.Updated: Annually The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This web map displays traffic count data provided by the City of Tempe Transportation Department. Data are symbolized by line thickness per each street section.Each segment's popup contains a weblink to historical traffic count data that are provided by the City of Tempe for public use.

Average Annual Daily Traffic data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain data on the total volume of vehicle traffic on a highway or road for a year divided by 365 days.

The City of Pasadena has a longstanding interest in protecting neighborhoods from cut-through traffic and speeding vehicles. As early as the 1980’s, the City authorized installation of speed humps to slow traffic in residential areas. Today, almost 400 of these traffic management devices have been installed along with many other traffic management measures.Traffic counts are conducted throughout the City of Pasadena either through resident requests, development projects, specific and general plans, or engineering studies. The Department of Transportation has collected these traffic counts and made them available to the public through the use of a Traffic Count Database.

Air Carrier Traffic: Passenger Load Factor data was reported at 85.850 % in Aug 2018. This records a decrease from the previous number of 87.460 % for Jul 2018. Air Carrier Traffic: Passenger Load Factor data is updated monthly, averaging 78.425 % from Jan 1996 (Median) to Aug 2018, with 272 observations. The data reached an all-time high of 87.460 % in Jul 2018 and a record low of 58.490 % in Sep 2001. Air Carrier Traffic: Passenger Load Factor data remains active status in CEIC and is reported by US Department of Transportation. The data is categorized under Global Database’s United States – Table US.TA008: Air Traffic Statistics.

As of the last quarter of 2023, 31.57 percent of web traffic in the United States originated from mobile devices, down from 49.51 percent in the fourth quarter of 2022. In comparison, over half of web traffic worldwide was generated via mobile in the last examined period.

The Traffic_Counts_Hourly feature class models the locations and hourly volume of traffic counts within the Pikes Peak Area Council of Governments (PPACG) region. The data in this feature class is developed by PPACG from information provided by or acquired from the Colorado Department of Transportation (CDOT), county and municipal governments within the region, and private companies contracted to perform traffic count collections.The 'Source_ID' field references the ID for the counter, location, or report provided by the source of each count, which may not be unique to the dataset. The 'RouteCL_ID' field stores the unique ID for a related Route_Centerlines feature class segment, and the 'NetLink_ID' field stores the unique ID for a related roadway network link. The 'Loc_Desc' field describes the relative location of the traffic counter, while the the 'Travel_Dir' field identifies which direction of traffic was collected at that location. The 'Count_Yr' field records the year the count was collected, while the 'AvgDayTot' field identifies the total Average Daily Traffic (ADT) count of all traffic at each location. The remaining fields store the average traffic count for each one-hour period throughout the day, the number of days the counter collected at each location, and identify the source of each traffic count.

Air Carrier Traffic: Revenue Passenger Enplanements data was reported at 81,411.000 Person th in Aug 2018. This records a decrease from the previous number of 84,307.000 Person th for Jul 2018. Air Carrier Traffic: Revenue Passenger Enplanements data is updated monthly, averaging 59,650.500 Person th from Jan 1996 (Median) to Aug 2018, with 272 observations. The data reached an all-time high of 84,307.000 Person th in Jul 2018 and a record low of 34,801.000 Person th in Sep 2001. Air Carrier Traffic: Revenue Passenger Enplanements data remains active status in CEIC and is reported by US Department of Transportation. The data is categorized under Global Database’s United States – Table US.TA008: Air Traffic Statistics.

Traffic sections define segments of roadway where traffic volume is homogeneous along each segment length, and the specific breakpoints where traffic volumes change. This segmentation of the roadway network is necessary for the assignment of point level traffic count information to GIS roadway segments and serve to support HPMS annual reporting and other planning purposes. The relationship between traffic count stations and traffic sections is defined in the traffic sections, and this link is critical in the creation, management, and use of all network traffic statistics and information. The spatial location of each traffic section and station is defined in ADOT’s GIS linear reference system.Traffic counts are generally collected at a single point along a section of roadway, and are commonly referred to as Count Locations, Sites, or Stations.Ideally, counts are taken at the same location (or nearby) periodically. The MS2 Traffic Count Database System (TCDS) allows traffic collection agencies to create or contribute to a database of traffic data, including count locations. ADOT also maintains a database of traffic count stations, which is reconciled with the TCDS. Traffic Count Stations are assigned to a Traffic Section through the Traffic Section ID. The Station"s ID can also be used in the calculation of traffic statistics for that Traffic Section, which is how it is utilized in analysis and reporting (such as HPMS).

The dataset contains the quarterly international traffic statistics in the regions in the form of city pairs in the category of passengers.

Data on road traffic by road and vehicle type, produced by Department for Transport.

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: 05/24/2025.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 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.

Total website visits to etsy.com peaked in November 2023, with over 650 million visits. Headquartered in New York, Etsy is a leading consumer-to-consumer (C2C) marketplace specialized in handmade crafts.

Facebook is a web traffic powerhouse: in March 2024 approximately 16.6 billion visits were measured to the Facebook.com, making it one of the most-visited websites online. In the third quarter of 2023, Facebook had nearly three billion monthly active users.

Traffic-related data collected by the Boston Transportation Department, as well as other City departments and State agencies. Various types of counts: Turning Movement Counts, Automated Traffic Recordings, Pedestrian Counts, Delay Studies, and Gap Studies.

~_Turning Movement Counts (TMC)_ present the number of motor vehicles, pedestrians, and cyclists passing through the particular intersection. Specific movements and crossings are recorded for all street approaches involved with the intersection. This data is used in traffic signal retiming programs and for signal requests. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

~_Automated Traffic Recordings (ATR)_ record the volume of motor vehicles traveling along a particular road, measures of travel speeds, and approximations of the class of the vehicles (motorcycle, 2-axle, large box truck, bus, etc). This type of count is conducted only along a street link/corridor, to gather data between two intersections or points of interest. This data is used in travel studies, as well as to review concerns about street use, speeding, and capacity. Counts are typically conducted for 12- & 24-Hr periods.

~_Pedestrian Counts (PED)_ record the volume of individual persons crossing a given street, whether at an existing intersection or a mid-block crossing. This data is used to review concerns about crossing safety, as well as for access analysis for points of interest. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

~_Delay Studies (DEL)_ measure the delay experienced by motor vehicles due to the effects of congestion. Counts are typically conducted for a 1-Hr period at a given intersection or point of intersecting vehicular traffic.

~_Gap Studies (GAP)_ record the number of gaps which are typically present between groups of vehicles traveling through an intersection or past a point on a street. This data is used to assess opportunities for pedestrians to cross the street and for analyses on vehicular “platooning”. Counts are typically conducted for a specific 1-Hr period at a single point of crossing.

This hosted feature layer has been published in RI State Plane Feet NAD 83.This data set was created for the Rhode Island Dept. of Transportation. This data set contains locations for the 24 hour average daily traffic counts on state maintained roads with information containing the station number, the segment of roadway the count was taken on, the city the count location is in and the actual 24 hour average counts for each location.This data set contains the annual 24 Hour Average Daily Traffic Count Locations on State maintained roads in Rhode Island for 2001.