The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

A collection of historic traffic count data and guidelines for how to collect new data for Massachusetts Department of Transportation (MassDOT) projects.

Attributes of sites in Hamilton City which collect anonymised data from a sample of vehicles. Note: A Link is the section of the road between two sites

Column_InfoSite_Id, int : Unique identiferNumber, int : Asset number. Note: If the site is at a signalised intersection, Number will match 'Site_Number' in the table 'Traffic Signal Site Location'Is_Enabled, varchar : Site is currently enabledDisabled_Date, datetime : If currently disabled, the date at which the site was disabledSite_Name, varchar : Description of the site locationLatitude, numeric : North-south geographic coordinatesLongitude, numeric : East-west geographic coordinates

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Disclaimer

Hamilton City Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the data released for public download. Levels, locations and dimensions of works depicted in the data may not be accurate due to circumstances not notified to Council. A physical check should be made on all levels, locations and dimensions before starting design or works.

Hamilton City Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.

While you are free to crop, export and re-purpose the data, we ask that you attribute the Hamilton City Council and clearly state that your work is a derivative and not the authoritative data source. Please include the following statement when distributing any work derived from this data:

‘This work is derived entirely or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'

Interactive map displaying average road traffic volumes for a selection of permanent Roads and Maritime Services roadside collection device stations across NSW. Figures will be updated annually.

Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates. planning and designing highways and other purposes.Traffic Census Program Page

HCAADT represents current (most recent) Heavy Commercial Annual Average Daily Traffic on sampled road systems. This information is displayed using the Traffic Count Locs Active feature class as of the annual HPMS freeze in January. Historical HCAADT is found in another table. Please note that updates to this dataset are on an annual basis, therefore the data may not match ground conditions or may not be available for new roadways. Resource Contact: John Hackett, Traffic Forecasting & Analysis (TFA), http://www.dot.state.mn.us/tda/contacts.html#TFA

Check other metadata records in this package for more information on Heavy Commercial Annual Average Daily Traffic Locations Information.


Link to ESRI Feature Service:

Heavy Commercial Annual Average Daily Traffic Locations in Minnesota: Heavy Commercial Annual Average Daily Traffic Locations

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: 07/12/2025.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

In Hamburg, event-related traffic counts are carried out at so-called on-demand counting stations. These event-related counts supplement the permanent traffic counts using infrared detectors or induction loops and are carried out, for example, in connection with traffic planning or investigations. The demand counts are usually manual counts, usually in the counting time from 6 a.m. to 7 p.m., which is carried out on representative normal working days. This data set contains the average daily motor vehicle traffic volumes determined in these event-related traffic censuses as a parameter of the average traffic load on a street cross-section. Using mathematical-statistical methods, a distinction is made between average values ​​for all days (DTV, Monday to Sunday) and all working days (DTVw, Monday to Friday). The traffic volumes of different up-to-dateness are available as point information. The georeferencing is carried out according to a schematic representation of the node geometry and is therefore not projected onto the road network in the correct position.

The Annual Average Daily Traffic (AADT) is the estimated mean daily traffic volume and the Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles. For continuous sites, estimates are calculated by summing the Annual Average Days of the Week and dividing by seven. For short-count sites, estimates are made by factoring a short count using seasonal and day-of-week adjustment factors.Data Coverage: The dataset covers the entire Federal Aid System in the State of Michigan.Update Cycle: AADT & CAADT volumes are created and released every year.Transportation Data Management System (TDMS) AADT Calculation HelpTraffic Monitoring Program

In Hamburg, event-related traffic counts are carried out at so-called demand counting points. These event-related counts supplement the permanent traffic counts using infrared detectors or induction loops and are carried out, for example, in connection with traffic planning or investigations.

The demand counts are usually manual counts, usually in the counting period from 6 to 19 Clock, which is carried out on representative normal working days.

This data set contains the average daily vehicle traffic volumes determined during these event-related traffic counts as a parameter for the average traffic load of a road cross-section. Using mathematical-statistical methods, a distinction is made between average values ​​for all days (DTV, Monday to Sunday) and all working days (DTVw, Monday to Friday).

The traffic volumes of different timeliness are available as point information. The georeferencing is carried out according to a schematic representation of the node geometry and is therefore not projected onto the road network in a true position.

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.

This dataset is historical. For recent data, we recommend using https://chicagotraffictracker.com. -- Average Daily Traffic (ADT) counts are analogous to a census count of vehicles on city streets. These counts provide a close approximation to the actual number of vehicles passing through a given location on an average weekday. Since it is not possible to count every vehicle on every city street, sample counts are taken along larger streets to get an estimate of traffic on half-mile or one-mile street segments. ADT counts are used by city planners, transportation engineers, real-estate developers, marketers and many others for myriad planning and operational purposes. Data Owner: Transportation. Time Period: 2006. Frequency: A citywide count is taken approximately every 10 years. A limited number of traffic counts will be taken and added to the list periodically. Related Applications: Traffic Information Interactive Map (http://webapps.cityofchicago.org/traffic/).

AADT represents current (most recent) Annual Average Daily Traffic on sampled road systems. This information is displayed using the Traffic Count Locations Active feature class as of the annual HPMS freeze in January. Historical AADT is found in another table. Please note that updates to this dataset are on an annual basis, therefore the data may not match ground conditions or may not be available for new roadways. Resource Contact: Christy Prentice, Traffic Forecasting & Analysis (TFA), http://www.dot.state.mn.us/tda/contacts.html#TFA

Check other metadata records in this package for more information on Annual Average Daily Traffic Locations Information.


Link to ESRI Feature Service:

Annual Average Daily Traffic Locations in Minnesota: Annual Average Daily Traffic Locations

The data set contains the traffic volumes on main roads (HVS) and federal motorways (BAB). Traffic volume map 2019: For the year 2019, the traffic volume is given as an average daily traffic volume (DTV, Monday to Sunday). In addition, the percentage of heavy traffic (SV) in the average daily traffic on weekdays (DTVw, Monday to Friday) is given in the attributes. The information on the traffic volumes comes from the traffic model of the city of Hamburg. The traffic model is based, among other things, on traffic counts that were carried out up to 2019. The traffic volumes (vehicles) stored in the traffic model as DTVw were converted to the DTV using flat-rate factors, then manually adjusted and smoothed if necessary. However, the data on heavy-duty traffic provided in the traffic model as the SV share of the DTVw was not converted to the DTV, but transferred to the DTV without adjustment. The information in the traffic volume map is not suitable for traffic forecasts. Processing status 2019: 22.11.2022 Traffic volume map 2014: For the years 2013 and 2014, the traffic volume is given as an average daily traffic volume on weekdays (DTVw, Monday to Friday). The information on the traffic volumes comes from traffic censuses that were carried out on federal motorways and main roads up to 2014. The counting results were extrapolated to the average weekday traffic (DTVw) for 2014. Due to extensive construction site influences in 2014, the DTVw values ​​of 2013 were used as a basis for the federal motorways. The volume of traffic can vary within the specified bandwidth within the colored route sections. The information in the traffic volume map is not suitable for traffic forecasts. Processing status 2013/2014: 08/25/2016

The Annual Average Daily Traffic (AADT) for sections of roads for all vehicle types, including single and combination trucks, reported in the 2023 Highway Performance Monitoring System (HPMS) federal report.Annual Average Daily Traffic (AADT) is used to represent vehicle traffic on a typical day of the year and is important for planning purposes, such as defining the federal functional classification of a roadway. The values are calculated using data collected from traffic counter devices, such as Automatic Traffic Recorders (ATR), Weigh In Motion (WIM) devices, and short term counters using tubes. All available traffic data collected throughout the year are then summed and divided by 365 to calculate the annual average daily traffic.Single unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 4 through 7. Combination unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 8 through 13. Refer to the Federal Highway Administration website for more information about truck classifications.Reported Extent: State Highway System (i.e. all ADOT-owned roads), National Highway System (NHS), and all federal aid-eligible roads. Federal aid-eligible roads include urban roads classified as minor collectors or above (functional system 1-6) and rural roads classified as major collectors or above (function system 1-5). Roads where ATRs are available, counts are updated annually. For roads where short term counters must be used, traffic counts are collected every three years for all National Highway System (NHS) roads as well as interstates (functional system 1), principal arterials (functional systems 2-3), and sample panel sections. All other federal aid-eligible roads, including minor arterials and collectors, are collected every six years.For undivided highways, which do not have a physical barrier between the two directions of traffic, values are reported as the sum total for both directions of travel. On divided highways, AADT is reported separately on the cardinal and non-cardinal directions of the roadway. Note, the cardinal direction refers to the direction of increasing mileposts.

Statewide Traffic Volume Historic and Forecast Historic traffic volume observations, future traffic volume forecasts, and adjustment factors -- are summarized using Utah's roadway planning summary segments -- for the Wasatch Front Regional Council metropolitan planning organization travel model area. This dataset can be viewed in an interactive map at: https://wfrc.org/traffic-volume-map/. This dataset provides segment level traffic volume data (historic estimates and future forecasts) within the state of Utah. Wasatch Front Regional Council (WFRC) metropolitan planning organization's travel model boundaries (including Salt Lake, Davis, western Weber, and southern Box Elder counties' urbanized areas). Future forecasts have been developed with the support of the Wasatch Front Travel Demand Model (v8.3.1) in conjunction with the adopted 2019 Regional Transportation Plan (RTP). This dataset was first released May 5th, 2020 (check the RELEASE field/column attribute for most recent update date). MAG travel model boundaries include the urbanized areas of Utah County. Cache travel model boundaries include Cache County. Dixie travel model boundaries include Washington County. Also contained within this dataset are adjustment factors, developed as part of a statewide effort led by UDOT, that can be used to scale the Average Annual Daily Traffic (AADT) volumes estimates and forecasts to provide more time-period specific volumes for a time period subsets (e.g. weekdays, weekends, specific months, seasons, maximum month, etc). Contact and additional information is available from https://wfrc.org/models-and-forecasting or through email contact to analytics@wfrc.org.UPDATE 12/31/2021: Highland Drive revised forecasts for SEGIDs 2082_009.0, 2082_009.6, 2082_011.5, 0152_002.5, 0152_002.8. Field names and descriptions are as follows: RELEASE (version of dataset) SEGID (Segment ID, combination of Route_ID and BMP) ROUTE_ID (Route Identification, <1000 for Interstate/State Routes, >1,000 for Federal Aid Routes) BMP (Begin Milepost, or milepost of beginning of segment) EMP (End Milepost, or milepost of ending of segment) FULLNAME (name of segment) CO_FIPS (County Federal Information Processing Standard, unique code for each county) CO_NAME (Name of county) X (Centroid of Segment, UTM Zone 12N) Y (Y Centroid of Segment, UTM Zone 12N) DISTANCE (length of segment in miles) F2050...F2024 (forecast AADT volumes for model years per 2019 RTP) CH17TO50...CH17TO19 (change in AADT volumes between model years) FNOTES (forecast notes, typically when drop or large increase in volumes) MOREINFO (url to more general information on models and forecasts) WFRC_FLG (flag value used internally by WFRC) AADT2017...AADT1981 (AADT estimates for a given year from UDOT) SUTRK2017 (Single-Unit, Box Type Truck percentage for 2017) CUTRK2017 (Combo-Unit, Semi Type Truck percentage for 2017) DOWFACFC (Day-of-Week Factor Functional Class) DOWFACAT (Day-of-Week Factor Area Type) FAC_MON...FAC_SUN (Day-of-Week factors for given days) FAC_WDAVG (Average Weekday Factor Monday-Thursday, multiply AADT by factor to get AWDT, divide AWDT by factor to get AADT) FAC_WEAVG (Average Weekend Factor Friday-Sunday) FAC_WEMAX (Max Weekend Factor Friday-Sunday) SSNGRP (Seasonal Factor Group) SSNVOLCLS (Seasonal Factor Volume Class) SSNATGROUP (Seasonal Factor Area Type Group) FAC_JAN...FAC_DEC (Month Factors, multiply AADT or AWDT get month ADT or AWDT) FAC_WIN (Winter Factor, December-February) FAC_SPR (Spring Factor, March-May) FAC_SUM (Summer Factor, June-August) FAC_FAL (Fall Factor, September-November) FAC_MAXMO (Month in which Maximum Month Factor is found) FAC_MAX (Maximum Month Factor)

Traffic Volumes from SCATS Traffic Management System Jan-Jun 2025 DCC. Published by Dublin City Council. Available under the license cc-by (CC-BY-4.0).Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road.

3 resources are provided:

SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows.

Information provided:

End Time: time that one hour count period finishes.

Region: location of the detector site (e.g. North City, West City, etc).

Site: this can be matched with the SCATS Sites file to show location

Detector: the detectors/ sensors at each site are numbered

Sum volume: total traffic volumes in preceding hour

Avg volume: average traffic volumes per 5 minute interval in preceding hour

All Dates Traffic Volumes Data

This file contains daily totals of traffic flow at each site location.

SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following;

Site id – This is a unique identifier for each junction on SCATS

Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets

Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets

Region – The area of the city, adjoining local authority, region that the site is located

LAT/LONG – Coordinates

Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends....

This data set contains the volume of bicycle traffic that was recorded as part of the "Stadtradeln" campaign of the Climate Alliance e.V. by users of the Stadtradeln app in the city of Hamburg in the years 2018 to 2020 in a 3-week period. The data set is an excerpt of a Germany-wide data set. This data set was processed as part of the MOVEBIS research project at the TU Dresden. This is an mFUND project of the Federal Ministry of Transport and Digital Infrastructure. The data is under the CC-BY-NC license, i.e. it may not be used for commercial purposes and the author must be named. The author is as follows: "Grubitzsch P., Lißner S., Huber S., Springer T., [2021] Technical University of Dresden, Professorship for Computer Networks and Professorship for Traffic Ecology". The grid basis onto which the data is projected comes from Open Street Maps. Only the traffic volumes for the city of Hamburg are included in the present dataset. The Germany-wide data (bicycle traffic volumes, speeds and heat maps) are available via the mCloud (see links). The data was processed for Hamburg, in particular for display in the municipal geoportals. The data is primarily used for a qualitative assessment of which roads are used by bicycle traffic and how much and whether there have been changes/shifts over the years, e.g. because bicycle traffic facilities have been renovated or newly built. The absolute figures, on the other hand, are not very meaningful, since they depend largely on the number of participants in the City Cycling campaign and have accordingly increased significantly over the years. It should also be noted that the participants in the Stadtradeln campaign and thus the routes used are not necessarily representative of the total population and cycling in the entire city.

Traffic count and speed data collected from the several Wavetronix radar sensors deployed by the City of Austin.

The Travel Sensor dataset ( https://data.austintexas.gov/Transportation-and-Mobility/Travel-Sensors/6yd9-yz29 ) is related to this dataset using the 'KITS ID' field. The Travel Sensors dataset provides more information on sensor location and status.