This map contains 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 TomTom (www.tomtom.com). Historical traffic is based on the average of observed speeds over the past year. 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 can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes. The map 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.

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

Vehicle traffic volumes for arterial streets in Seattle based on spot studies that have been adjusted for seasonal variation.

| Additional Information: 2019 Traffic Report(will be published fall 2019)
| Attribute Information: 2018_Traffic_Flow_Counts_OD.pdf

| Update Cycle: As Needed
| Contact Email: DOT_IT_GIS@seattle.gov

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

The Nebraska Department of Transporation (NDOT) collects traffic data including traffic flow, traffic counts, and truck traffic flow. The data is averaged out on a yearly basis, and is reported bi-annually, with the first year in the application being 2016. The application includes a filter widget that allows the user to filter the data based on the year that the traffic count was performed. The default filter is set for the most recent iteration of traffic count data, and if there is no filter applied, users can view data for all years by clicking on the features and reading the popup.Maps using this layer (as of 3/20/2023)AADTFlow_MapAADT Flow Map over 6,000UAS Request Webmap - UAS TeamThis item is shared with the following groups:PublicDepartment of TransportationDOT AD 100 HigherDOT DevelopersOther associated items:App -Annual Average Daily Traffic FlowMap -AADTFlow_MapMap Image Layer -AADTFlow_DOT_NE

Displays vehicle traffic volumes for arterial streets in Seattle based on spot studies that have been adjusted for seasonal variation. Data is a one time snapshot for 2022 and is maintained by Seattle Department of Transportation.Contact: Traffic OperationsRefresh Cycle: None, Snapshot for 2022 Only.

Web application for traffic flows for state road networks.

Traffic flows show the total traffic of motor vehicles and truck traffic with different bandwidths where the width of the bands is proportional to the average annual traffic.

Average annual weekday traffic volumes used to produce the SDOT Traffic Flow Map

Average weekday traffic counts (AWT) are collected at count stations throughout the city and represent the daily average for Monday-Friday traffic volume. Count stations in the eastern section of the city are collected in even numbered years, while those in the city's western section are collected in odd numbered years. Field descriptions/definitions for traffic count data as follows: ObjectID: GIS auto-generated unique identifiermslink: mslink of street segmentsegment_na: street segment nameSTATION: count station numberSOURCE: designates segment with counter or linkedSTATION: volume count station numberSOURCE: volume count station or linked segmentAWT_Count: most recent average weekday traffic countAWT_Yr: year of most recent countShape: GIS geometry typeYear_Txt: year of most recent count (text field)Shape.STLength(): GIS calculated segment length

Displays vehicle traffic volumes for arterial streets in Seattle based on spot studies that have been adjusted for seasonal variation. Data is a one time snapshot for 2019 and is maintained by Seattle Department of Transportation.Contact: Traffic OperationsRefresh Cycle: None, Snapshot for 2019 Only.

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).**

This map contains 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. The real-time 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 color coded map leverages historical, real time and predictive traffic data. Historical traffic is based on the average of observed speeds over the past three years. A color coded traffic map can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes. The map 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.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.

The traffic counts shown on this map represent estimates of the Annual Average Daily Traffic (AADT) for the most recent full year. These AADT's are derived mainly from 24-hour volumes recorded by portable traffic counters. These short-term counts are adjusted for day-of-week and seasonal variations using data from 80 continuous permanent counters. An axle correction factor has been applied to each short-term count. Heavy commercial volumes are derived from short-term vehicle classification counts.For an assortment of count maps, please visit Traffic Count Maps. More information about the Kansas Department of Transportation (KDOT) can be found at the following URL: ksdot.org.

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.

With the forecast increase in air traffic demand over the next decades, it is imperative to develop tools to provide traffic flow managers with the information required to support decision making. In particular, decision-support tools for traffic flow management should aid in limiting controller workload and complexity, while supporting increases in air traffic throughput. While many decision-support tools exist for short-term traffic planning, few have addressed the strategic needs for medium- and long-term planning for time horizons greater than 30 minutes. This paper seeks to address this gap through the introduction of 3D aircraft proximity maps that evaluate the future probability of presence of at least one or two aircraft at any given point of the airspace. Three types of proximity maps are presented: presence maps that indicate the local density of traffic; conflict maps that determine locations and probabilities of potential conflicts; and outliers maps that evaluate the probability of conflict due to aircraft not belonging to dominant traffic patterns. These maps provide traffic flow managers with information relating to the complexity and difficulty of managing an airspace. The intended purpose of the maps is to anticipate how aircraft flows will interact, and how outliers impact the dominant traffic flow for a given time period. This formulation is able to predict which "critical" regions may be subject to conflicts between aircraft, thereby requiring careful monitoring. These probabilities are computed using a generative aircraft flow model. Time-varying flow characteristics, such as geometrical configuration, speed, and probability density function of aircraft spatial distribution within the flow, are determined from archived Enhanced Traffic Management System data, using a tailored clustering algorithm. Aircraft not belonging to flows are identified as outliers.

This contains data maintained by SDOT that is related to the study of traffic patterns in the city. The volumes in the data represent the Average Annual Weekday Traffic (AAWDT) (5-day, 24-hour) for that section of roadway. | Attribute Information: https://www.seattle.gov/Documents/Departments/SDOT/GIS/2009_Traffic_Flow_Counts_OD.pdf | Update Cycle: As Needed | Contact Email: DOT_IT_GIS@seattle.gov

This contains data maintained by SDOT that is related to the study of traffic patterns in the city. The volumes in the data represent the Average Annual Weekday Traffic (AAWDT) (5-day, 24-hour) for that section of roadway.

| Attribute Information: https://www.seattle.gov/Documents/Departments/SDOT/GIS/2007_Traffic_Flow_Counts_OD.pdf

| Update Cycle: As Needed
| Contact Email: DOT_IT_GIS@seattle.gov

Geometry describing traffic flows. Line geometry. For municipal road network only. Operations Analysis & Dialogue, Traffic Planning, Traffic Office. The traffic flow map contains data on traffic volumes in Stockholm divided into light and heavy vehicles, per daily average day and for a certain period of time over the day. Data refer to 2014-2015, which means that Norra Länken is not included . The traffic volumes are compiled by the Traffic Office from several different sources including the company's own measurements, the congestion tax system, the MCS system (Motorway Control System) on E4/E18/E20 and others. The traffic flow map is comprehensive, which means that a large proportion of the road network has interpolated traffic volumes, or standard values. It mainly concerns low-traffic road networks in, for example, residential areas. Interpolation means that streets without measured flows are assigned a flow depending on the surrounding streets that have measured traffic volumes. The percentage in parentheses is the share of heavy traffic. Traffic volumes in the north-east inner city should be checked with the Traffic Office

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit in 2022. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.For more information, please visit MDOT Traffic Monitoring Program.