Traffic count data downloaded from GDOT public map here: https://gdottrafficdata.drakewell.com/publicmultinodemap.aspRetrieved Annual Statistics Reports: "All Station AADT and Truck Percent Statistics." Mapped by Lat/Long field.Retrieved and rehosted for staff use and overlay on city maps on 12/14/2018."The Georgia Department of Transportation’s Traffic Analysis and Data Application (TADA!) website presents data collected from the Georgia Traffic Monitoring Program located on the public roads in Georgia. The Website uses a dynamic mapping interface to allow the User to access data from the map as well as in a variety of report, graph, and data export formats."

Retirement Notice: This item is in mature support as of June 2023 and will be retired in December 2025. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item.This layer shows traffic counts in the United States in a multiscale map. Traffic counts are widely used for site selection by real estate firms and franchises. Traffic counts are also used by departments of transportation for highway funding. This map is best viewed at large scales where you can click on each point to access up to five different traffic counts over time. At medium to small scales, comparisons along major roads are possible. The Business Basemap has been added to provide context at medium and small scales. It shows the location of businesses in the United States and helps to understand where and why traffic counts are collected and used. The pop-up is configured to display the following information:The most recent traffic countThe street name where the count was collectedThey type of count that was taken. See the methodology document for definitions of count types such as AADT - Average Annual Daily Traffic. Traffic Counts seasonally adjusted to represent the average day of the year. AADT counts represent counts taken Sunday—Saturday.A graph displaying up to five traffic counts taken at the same location over time. Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

GeorgiaNetworkTraffic2024: Traffic data for selected Georgia road segments for 2024. Data obtained from GDOT in 2025 and updated Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT, VMT and Truck VMT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2022-2024: This layer shows traffic counts in the greater Chattanooga region compiled by GT from state sources. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.TNPedestrianLevelTrafficStress: Pedestrian LTS is a model for roadway walkability and accessibility based on a weighted average from infrastructure and traffic conditions. These criteria include: lane count, AADT, speed limit, sidewalk presence, sidewalk width, shoulder presence, raised median presence, and roadway illumination. TDOT only has asset data (sidewalks, shoulders, medians) for TDOT-maintained assets, so, roads that lacked this data had those fields marked Null and were given a seperate weighted average based on lane count, AADT, speed limit, and illumination data. Roads which lacked lane count, AADT, or speed limit data were excluded from the analysis. Data subset to the Thrive region in November 2025TNNetworkTraffic2024:This dataset contains geospatial line data showing Annual Average Daily Traffic (AADT), Vehicle Miles Traveled (VMT), calculation methods for all AADTs, Truck Percentages, and the TN-TIMES link for the station. The dataset also references some features of the roadway, such as functional class, state ownership, urban boundary, and more, as they were assigned to the linear network for the 2024

Georgia_Average_Annual_Daily_Trafffic_2022: Traffic data for selected Georgia road segments between 2020-222. Data obtained from GDOT in 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2019-2022: This layer shows traffic counts in the greater Chattanooga region compiled by ESRI. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.GaRoad Network Truck 2020: Traffic data for selected Georgia road segments in 2020. Data obtained from GDOT in May 2022. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataTN Road Network Traffic 2022: Traffic data for selected TN road segments in 2020-2022. Data obtained from TDOT in May 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT.

This layer contains points that highlight traffic counting locations with their associated traffic count observations over several years since 2013 within the City of Johns Creek, GA.Data Note: In 2020, only one direction of traffic was recorded for locations #19, 28, and 34. In the data contained in this layer, that single direction count was duplicated to make year to year comparisons more accurate.

Traffic count from 8 counters located around Calderdale. Please note

Sdate - indicates the date and time the count was taken. Cosit - camera ID number which indicates the camera location (see Counter Locations document below). Period - length of time count was taken. LaneNumber - Lane ID number which indicates the number of lanes. LaneDirection - the number of directions the lane or lanes go. Direction - the direction of the lane. Volume - the number of vehicles counted, if the number is negative the count has been discarded. Flag Text - Additional information e.g. roadworks, holiday, etc

The Traffic count dashboard is a visualisation of this raw data split by full year count and snapshot count of vehicles at each counter location.

Georgia_Average_Annual_Daily_Trafffic_2022: Traffic data for selected Georgia road segments between 2020-222. Data obtained from GDOT in 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2019-2022: This layer shows traffic counts in the greater Chattanooga region compiled by ESRI. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.GaRoad Network Truck 2020: Traffic data for selected Georgia road segments in 2020. Data obtained from GDOT in May 2022. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataTN Road Network Traffic 2022: Traffic data for selected TN road segments in 2020-2022. Data obtained from TDOT in May 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT.

This layer contains all aspects of the physical traffic signal infrastructure present in the City of Johns Creek, GA.Traffic signal heads: actual traffic signals in the CityLight sign locations: locations of all lighted signsSignal masts and wires: locations of all mast arms and wires that hold traffic signal heads and other signagePedestrian controls and signals: locations of all pedestrian controls and signalsTraffic cameras: locations of all traffic camerasSignal cabinets: locations of all signal cabinets containing ITS infrastructureTraffic counting locations: locations of all traffic counting infrastrucutureTraffic signal pucks: locations of all traffic pucks that have been installed

This layer contains traffic jams detected by Waze that have been aggregated to street data for Johns Creek, GA. By aggregating the tiny and/or inconsistently sized jams to larger portions of roadway, traffic analysis can be done more accurately. Data is updated every 5 minutes continuously.

Turkey Central Govt: RE: GB: SF: PA: GA: Traffic Insurance Shares data was reported at 0.000 TRY th in Jun 2018. This records an increase from the previous number of -28,586.000 TRY th for May 2018. Turkey Central Govt: RE: GB: SF: PA: GA: Traffic Insurance Shares data is updated monthly, averaging 12,170.500 TRY th from Jan 2006 (Median) to Jun 2018, with 150 observations. The data reached an all-time high of 62,118.000 TRY th in Jan 2017 and a record low of -28,586.000 TRY th in May 2018. Turkey Central Govt: RE: GB: SF: PA: GA: Traffic Insurance Shares data remains active status in CEIC and is reported by General Directorate of Public Accounts. The data is categorized under Global Database’s Turkey – Table TR.F003: Central Government Budget: Revenue: Ministry of Finance.

Zykluszähler-Standorte innerhalb des Verwaltungsgebiets Dún Laoghaire-Rathdown.

Diese Dateien enthalten Daten zum Standort von sechzehn Zykluszählern. Weitere Informationen umfassen die Art des aufgezeichneten Verkehrs (Radfahrer/Fußgänger), Startdatum, aufgezeichnete Richtung und ITM-Koordinaten. Orte sind nur indikativ und können aktualisiert werden.

Road Traffic Volumes of Private Cars

Raw Data of Traffic Flow Hour by Hour for Ardgillan Castle and Gardens for 2022

Dataset related to Torre Pacheco municipality. Traffic level measurements in Torre Pacheco main avenues, October 2024.

Passenger and freight traffic on railways (monthly).

Dieser Datensatz enthält Informationen zu Ampelanlagen aus dem Projekt OpenStreetMap.

Die Aktualisierung der Daten erfolgt wöchentlich. Es werden auch immer einige historische Daten zur Verfügung gestellt. Daher ist das Datum der Daten zu beachten.

Verwendete Tags von OpenStreetMap:

• highway = traffic_signals

Dromchla arb ionann é agus an chuid de bhóthar a úsáidtear le haghaidh gnáththrácht feithiclí.

------Datensatz veraltet-----------Derzeit werden die Daten für den Knoten 2150 nicht aktualisiert----Der Datensatz umfasst LSA-Prozessdaten für vier Knoten in Hamburg und enthält in Echtzeit aktuelle Signalausprägungen. Zusätzlich werden Daten zu Detektoren wie Fahrrad, Fußgänger, Kfz- Anforderungen sowie Busmeldungen übertragen. Hinweise zur Latenz: 4 Minuten Auflistung der Knoten: - 413: An Der Verbindungsbahn / Bundesstraße- 279: Edmund-Siemers-Allee / Grindelallee- 271: Theodor-Heuß-Platz / Edmund-Siemers-Allee- 2150: Edmund-Siemers-Allee / CCHWeitere Informationen zum Echtzeitdienst:Der OGC SensorThings API konforme Echtzeitdatendienst enthält Datenströme und Positionen von Fahrspurbeziehungen an Kreuzungen mit Lichtsignalanlagen für Fahrradfahrer, Fußgänger sowie Kraftfahrzeuge im Hamburger Stadtgebiet. Wenn an der Lichtsignalanlage bereitgestellt, werden folgende Datenströme als JSON-Objekte ausgeliefert: Primärsignale, Sekundärsignale, Hilfssignale, Akustiksignale, KFZ-Signalanforderungen, Fahrradfahrersignalanforderungen, Fußgängersignalanforderungen, Akustiksignalanforderung, ÖPNV-Voranmeldung, ÖPNV-Anmeldung, ÖPNV-Abmeldung, Signalstaus und Wellensekunde. In der OGC SensorThings API sind die Informationen zu den Fahrspurbeziehungen in der Entität Thing hinterlegt. Für die oben aufgelisteten Datenströme, die an einem konkreten Thing verfügbar sind, wird ein Eintrag in der Entität Datastreams erstellt der das entsprechende Thing referenziert. Alle Zeitangaben sind in der koordinierten Weltzeit (UTC) angegeben.In der Entität Datastreams gibt es im JSON-Objekt unter dem "key" "properties" weitere "key-value-Paare". In Anlehnung an die Service- und Layerstruktur im GIS haben wir Service und Layer als zusätzliche "key-value-Paare" unter dem JSON-Objekt properties eingeführt.Hier ein Beispiel:{"properties":{"serviceName": "HH_STA_traffic_lights","layerName": "primay_signal","key":"value"}}Mögliche values für “layerName”: * primay_signal (Primärsignal), * secondary_signal (Sekundärsignal), * auxiliary_signal (Hilfssignal), * acoustic_signal (Akustiksignal), * detector_car (KFZ-Signalanforderung), * detector_cyclist (Fahrradfahrersignalanforderung), * detector_pedestrian (Fußgängersignalanforderung), * detector_acoustic_traffic_request (Akustiksignalanforderung), * bus_pre_request_point (ÖPNV-Voranmeldung), * bus_request_point (ÖPNV-Anmeldung), * bus_checkout (ÖPNV-Abmeldung), * signal_program (Signalprogrammstatus), * cycle_second (Wellensekunde)Mit Hilfe dieser "key-value-Paare" können dann Filter für die REST-Anfrage definiert werden, bspw.https://iot.hamburg.de/v1.0/Datastreams?$filter=properties/serviceName eq 'HH_STA_traffic_lights' and properties/layerName eq 'primary_signal'Die Echtzeitdaten kann man auch über einen MQTT-Broker erhalten. Die dafür notwendigen IDs können über eine REST-Anfrage bezogen werden und dann für das Abonnement auf einen Datastream verwendet werden:MQTT-Broker: iot.hamburg.deTopic: v1.0/Datastreams({id})/Observations