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.

Real Time Traffic Data Market Outlook

The global real-time traffic data market size is anticipated to reach USD 15.3 billion by 2032 from an estimated USD 6.5 billion in 2023, exhibiting a robust CAGR of 10.1% over the forecast period. This substantial growth is driven by the increasing need for efficient traffic management systems and the rising adoption of smart city initiatives worldwide. Governments and commercial entities are investing heavily in advanced technologies to optimize traffic flow and enhance urban mobility, thus fostering market expansion.

The surge in urbanization and the consequent rise in vehicle ownership have led to severe traffic congestion issues in many metropolitan areas. This has necessitated the implementation of real-time traffic data systems that can provide accurate and timely information to manage traffic effectively. With the integration of sophisticated technologies such as IoT, AI, and big data analytics, these systems are becoming more efficient, thereby driving market growth. Furthermore, the growing emphasis on reducing carbon emissions and enhancing road safety is also propelling the adoption of real-time traffic data solutions.

Technological advancements are playing a pivotal role in shaping the real-time traffic data market. Innovations in sensor technology, the proliferation of GPS devices, and the widespread use of mobile data are providing rich sources of real-time traffic information. The ability to integrate data from multiple sources and deliver actionable insights is significantly enhancing traffic management capabilities. Additionally, the development of cloud-based solutions is enabling scalable and cost-effective deployment of traffic data systems, further contributing to market growth.

Another critical growth factor is the increasing investment in smart city projects. Governments across the globe are prioritizing the development of smart transportation infrastructure to improve urban mobility and reduce traffic-related issues. Real-time traffic data systems are integral to these initiatives, providing essential data for optimizing traffic flow, enabling route optimization, and enhancing public transport efficiency. The involvement of private sector players in these projects is also fueling market growth by introducing innovative solutions and fostering public-private partnerships.

The exponential rise in Mobile Data Traffic is another significant factor influencing the real-time traffic data market. As more people rely on smartphones and mobile applications for navigation and traffic updates, the demand for real-time data has surged. Mobile data provides a wealth of information about traffic patterns and congestion levels, enabling more accurate and timely traffic management. The integration of mobile data with other data sources, such as GPS and sensor data, enhances the overall effectiveness of traffic data systems. This trend is particularly evident in urban areas where mobile devices are ubiquitous, and the need for efficient traffic management is critical. The ability to harness mobile data for traffic insights is driving innovation and growth in the market, as companies develop new solutions to leverage this valuable resource.

Regionally, North America and Europe are leading the market due to their early adoption of advanced traffic management technologies and significant investments in smart city projects. However, the Asia Pacific region is expected to witness the highest growth rate over the forecast period, driven by rapid urbanization, increasing vehicle ownership, and growing government initiatives to develop smart transportation infrastructure. Emerging economies in Latin America and the Middle East & Africa are also showing promising growth potential, fueled by ongoing infrastructure development and increasing awareness of the benefits of real-time traffic data solutions.

Component Analysis

The real-time traffic data market by component is segmented into software, hardware, and services. Each component plays a crucial role in the overall functionality and effectiveness of traffic data systems. The software segment includes traffic management software, route optimization software, and other analytical tools that help process and analyze traffic data. The hardware segment comprises sensors, GPS devices, and other data collection tools. The services segment includes installation, maintenance, and consulting services that support the deployment and operation of traffic data systems

Description

This dataset contains hourly data on the traffic volume for westbound I-94, a major interstate highway in the US that connects Minneapolis and St Paul, Minnesota. The data was collected by the Minnesota Department of Transportation (MnDOT) from 2012 to 2018 at a station roughly midway between the two cities.

Key Features

• holiday: a categorical variable that indicates whether the date is a US national holiday or a regional holiday (such as the Minnesota State Fair).
• temp: a numeric variable that shows the average temperature in kelvin.
• rain_1h: a numeric variable that shows the amount of rain in mm that occurred in the hour.
• snow_1h: a numeric variable that shows the amount of snow in mm that occurred in the hour.
• clouds_all: a numeric variable that shows the percentage of cloud cover.
• weather_main: a categorical variable that gives a short textual description of the current weather (such as Clear, Clouds, Rain, etc.).
• weather_description: a categorical variable that gives a longer textual description of the current weather (such as light rain, overcast clouds, etc.).
• date_time: a datetime variable that shows the hour of the data collected in local CST time.
• traffic_volume: a numeric variable that shows the hourly I-94 reported westbound traffic volume.

Potential Use Cases

The dataset can be used for regression tasks to predict the traffic volume based on the weather and holiday features. It can also be used for exploratory data analysis to understand the patterns and trends of traffic volume over time and across different conditions.

The global real-time traffic data market, valued at USD 36,900 million in 2025, is projected to reach USD 102,400 million by 2033, exhibiting a CAGR of 12.5% during the forecast period. The increasing adoption of smart transportation systems, rising urbanization, and growing demand for fleet management solutions drive market growth. Additionally, the widespread use of smartphones and the integration of GPS technology into vehicles are contributing to the generation of vast amounts of real-time traffic data. These factors indicate a promising future for the market, with continued growth expected in the coming years. Various types of real-time traffic data are available in the market, including traffic data, mobility data, and car traffic data. The traffic data segment accounted for the largest market share in 2025 and is anticipated to maintain dominance throughout the forecast period. Increasing government initiatives to improve traffic management and reduce congestion are key drivers behind the growth of this segment. Moreover, the rising demand for navigation and location-based services among consumers is boosting the market for real-time traffic data. Prominent companies in the market include TomTom, Otonomo, Datarade, HERE, Live Traffic Data, Mapbox, Intellias, INRIX, Factori, Gravy Analytics, PREDIK, Pixta, Datalastic, Grepsr, and SafeGraph. These companies offer a range of solutions and services to cater to the diverse needs of various industries and applications.

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."

Congestion, Traffic Average Speed, Travel TIme and Congestion Data Type Profile:

• Congestion levels per road segment in monthly averages
• Average speed in 15 minute and hourly intervals per roadway
• Travel time in seconds in 15 minute intervals per roadway
• Congested roadway segments based on travel time reliability in monthly intervals per roadway
• 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
• Traffic Impact 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

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

Unlock the Potential of Your Web Traffic with Advanced Data Resolution

In the digital age, understanding and leveraging web traffic data is crucial for businesses aiming to thrive online. Our pioneering solution transforms anonymous website visits into valuable B2B and B2C contact data, offering unprecedented insights into your digital audience. By integrating our unique tag into your website, you unlock the capability to convert 25-50% of your anonymous traffic into actionable contact rows, directly deposited into an S3 bucket for your convenience. This process, known as "Web Traffic Data Resolution," is at the forefront of digital marketing and sales strategies, providing a competitive edge in understanding and engaging with your online visitors.

Comprehensive Web Traffic Data Resolution Our product stands out by offering a robust solution for "Web Traffic Data Resolution," a process that demystifies the identities behind your website traffic. By deploying a simple tag on your site, our technology goes to work, analyzing visitor behavior and leveraging proprietary data matching techniques to reveal the individuals and businesses behind the clicks. This innovative approach not only enhances your data collection but does so with respect for privacy and compliance standards, ensuring that your business gains insights ethically and responsibly.

Deep Dive into Web Traffic Data At the core of our solution is the sophisticated analysis of "Web Traffic Data." Our system meticulously collects and processes every interaction on your site, from page views to time spent on each section. This data, once anonymous and perhaps seen as abstract numbers, is transformed into a detailed ledger of potential leads and customer insights. By understanding who visits your site, their interests, and their contact information, your business is equipped to tailor marketing efforts, personalize customer experiences, and streamline sales processes like never before.

Benefits of Our Web Traffic Data Resolution Service Enhanced Lead Generation: By converting anonymous visitors into identifiable contact data, our service significantly expands your pool of potential leads. This direct enhancement of your lead generation efforts can dramatically increase conversion rates and ROI on marketing campaigns.

Targeted Marketing Campaigns: Armed with detailed B2B and B2C contact data, your marketing team can create highly targeted and personalized campaigns. This precision in marketing not only improves engagement rates but also ensures that your messaging resonates with the intended audience.

Improved Customer Insights: Gaining a deeper understanding of your web traffic enables your business to refine customer personas and tailor offerings to meet market demands. These insights are invaluable for product development, customer service improvement, and strategic planning.

Competitive Advantage: In a digital landscape where understanding your audience can make or break your business, our Web Traffic Data Resolution service provides a significant competitive edge. By accessing detailed contact data that others in your industry may overlook, you position your business as a leader in customer engagement and data-driven strategies.

Seamless Integration and Accessibility: Our solution is designed for ease of use, requiring only the placement of a tag on your website to start gathering data. The contact rows generated are easily accessible in an S3 bucket, ensuring that you can integrate this data with your existing CRM systems and marketing tools without hassle.

How It Works: A Closer Look at the Process Our Web Traffic Data Resolution process is streamlined and user-friendly, designed to integrate seamlessly with your existing website infrastructure:

Tag Deployment: Implement our unique tag on your website with simple instructions. This tag is lightweight and does not impact your site's loading speed or user experience.

Data Collection and Analysis: As visitors navigate your site, our system collects web traffic data in real-time, analyzing behavior patterns, engagement metrics, and more.

Resolution and Transformation: Using advanced data matching algorithms, we resolve the collected web traffic data into identifiable B2B and B2C contact information.

Data Delivery: The resolved contact data is then securely transferred to an S3 bucket, where it is organized and ready for your access. This process occurs daily, ensuring you have the most up-to-date information at your fingertips.

Integration and Action: With the resolved data now in your possession, your business can take immediate action. From refining marketing strategies to enhancing customer experiences, the possibilities are endless.

Security and Privacy: Our Commitment Understanding the sensitivity of web traffic data and contact information, our solution is built with security and privacy at its core. We adhere to strict data protection regulat...

The dataset represents synthetic traffic data for a certain location over a one-year period. It includes information about the traffic volume, weather conditions, and special events that may affect traffic.

Features:

Timestamp: The date and time of the observation.Weather: The weather condition at the time of the observation (e.g., Clear, Cloudy, Rain, Snow).

Events: A binary variable indicating whether there was a special event affecting traffic at the time of the observation (True or False).

Traffic Volume: The volume of traffic at the location at the time of the observation.

The dataset is intended for use in analyzing traffic patterns and trends, as well as for developing and testing models related to traffic prediction and management.

Traffic-related delays are a major drain on the US economy, costing around $100 billion annually, rivaling the price tag of NASA's Artemis moon rocket. Therefore, real-time traffic information providers, expected to earn $5.6 billion in 2024, provide valuable solutions that help keep the economy moving. These systems source manifold data from phones, cameras, car manufacturers, event planners, and civil engineers. This vital information is then processed and sold to navigation apps, governments, or even back to the companies that provided it. Growth in this industry has surged at a compound annual growth rate (CAGR) of 10/2% over the last five years, largely driven by smarter systems becoming commonplace in smartphones and vehicles. Technological innovations have dramatically streamlined traffic management and monitoring while keeping profit margins healthy. Due to a rise in GPS-enabled phones and vehicle devices, traffic information is increasingly accurate and up-to-date. Smartphones have enhanced the spread of traffic data and enabled the extensive collection of live location information, aiding event and weather-related transport planning. Alongside this, roadside camera tech has evolved to identify cars and their speeds and count and categorize vehicles on the road, all without human help. Over the next five years, the industry will continue its upward trajectory, with a predicted CAGR of 2.0%, generating $6.2 billion by 2029. The easing of restrictive monetary policy will likely boost sales of cars equipped with navigation and traffic tools. Nevertheless, experts predict a slowdown if issues linked to the adverse effects of private vehicles take precedence over traditional car culture. In these changing times, it is clear that traffic systems hold vital importance, offering crucial guidance to communities at the planning level and for drivers.

LADOT automated and manual traffic count summary data for intersections throughout Los Angeles. Manual counts ("MAN" under the "Type" column) are generally 6-hr counts which have been expanded using a conversion factor.

Traffic Analysis Zones (TAZ) for the COG/TPB Modeled Region from Metropolitan Washington Council of Governments. The TAZ dataset is used to join several types of zone-based transportation modeling data. For more information, visit https://plandc.dc.gov/page/traffic-analysis-zone.

The real-time traffic data market, currently valued at $36.9 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 12.5% from 2025 to 2033. This significant expansion is fueled by several key factors. The increasing adoption of connected vehicles and the rise of smart city initiatives are driving demand for accurate and timely traffic information. Furthermore, the logistics and transportation sectors heavily rely on real-time data for efficient route optimization, delivery scheduling, and fleet management, contributing substantially to market growth. Government agencies are also significant consumers, leveraging this data for urban planning, traffic management, and emergency response systems. The market is segmented by application (Government, Logistics, Infrastructure Construction, Automobile, and Other) and data type (Traffic Data, Mobility Data, Car Traffic Data), with the Government and Logistics segments exhibiting particularly strong growth potential due to their increasing reliance on data-driven decision-making. Technological advancements such as improved sensor technologies and the development of sophisticated analytical tools are further enhancing the capabilities and accuracy of real-time traffic data solutions. Competitive dynamics within the real-time traffic data market are characterized by a mix of established players and emerging technology companies. Key players like TomTom, HERE Technologies, and INRIX are leveraging their existing mapping and navigation expertise to provide comprehensive real-time traffic data solutions. However, newer companies are entering the market with innovative data aggregation and analysis techniques, leading to increased competition and potentially lower prices. The geographic distribution of market share is expected to be dominated by North America and Europe initially, given the higher adoption rates of smart city technologies and connected vehicle infrastructure in these regions. However, rapid infrastructure development and increasing urbanization in Asia-Pacific are projected to drive substantial market growth in this region over the forecast period. The market's continued growth hinges on continued investment in smart city infrastructure, the expanding adoption of connected car technology, and the continuous development of more sophisticated data analytics.

The real-time traffic data market is experiencing robust growth, driven by the increasing need for efficient transportation management and urban planning. This market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors. The proliferation of connected vehicles and the rise of smart cities are generating massive volumes of traffic data, creating a high demand for real-time insights. Government agencies are increasingly leveraging this data for optimizing traffic flow, improving infrastructure, and enhancing public safety. Furthermore, the logistics and automotive sectors are benefiting from improved route planning, fleet management, and predictive maintenance capabilities enabled by real-time traffic data. The market's segmentation, encompassing various data types (traffic data, mobility data, car traffic data) and applications (government, logistics, infrastructure construction, automobile), reflects its diverse utility across multiple industries. The continued expansion of this market is expected to be driven by advancements in data analytics, the adoption of 5G technology enabling faster data transmission, and the growing integration of IoT devices in vehicles and infrastructure. However, challenges remain, including data privacy concerns, the high cost of data acquisition and processing, and the need for robust data security measures to maintain the integrity and reliability of the information. Competition among established players like TomTom, HERE, and INRIX, and the emergence of innovative startups, is likely to further shape market dynamics and accelerate innovation in data processing and analytical tools within the foreseeable future. Specific regional growth will vary, with North America and Europe currently dominating the market share, while Asia-Pacific is anticipated to experience the fastest growth due to rapid urbanization and technological advancements in the region.

Segmented traffic data for year 2018. The Traffic Analysis Section collects and compiles traffic data for the WVDOT. The data contains Route_ID,Begin_Point, End_Point, Section_Length and Value name. Data is current as of June 30, 2019 and updated as need Coordinate System: NAD_1983_UTM_Zone_17N

More Metadata

This layer contains the geographical boundaries of the Metropolitan Washington Council of Government's Traffic Analysis Zones (TAZ) of Loudoun County, Virginia. TAZs are designed to be relatively homogeneous units with respect to population, economic, and transportation characteristics. These TAZ boundaries were delineated by Loudoun County Government and adopted by the Metropolitan Washington Council of Governments.

Average daily traffic count data collected by each district for USDOT FHWA funding or roadways and infrastructure within West Virginia that is segmented by pre-defined mileage points from Federal Highway Administration (FHWA) onto the WVDOT road network. As with the AADT traffic counts, the data is collected in the field by traffic counters (Permanent, Special, or Short Term) by the districts in sent to the Traffic Analysis Section for further analysis and validation. The data is then evented onto the state highway network to create each roadway segment. Information contained in this data set includes station number, route number, route common name (if applicable), federal functional classification, RouteID, Route segment measurement, nearest city, year measured, number of trucks, collection apparatus type. Data is current as of July 1, 2021 and updated annually.

Analysis of ‘Weekly traffic data: speed 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/https-www-gipuzkoairekia-eus-es-datu-irekien-katalogoa-opendatasearcher-detail-detailview-5df16db8-c389-463b-b14c-731a1adfd6f1 on 17 January 2022.

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

Data distributed by hours, vehicle type and lane of several permanent seating stations available on the roads of the Gipuzkoa Provincial Council

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

Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

Snapshot img

Intelligent Traffic Management Market Size 2025-2029

The intelligent traffic management market size is forecast to increase by USD 24.01 billion at a CAGR of 14.8% between 2024 and 2029.

The market is experiencing significant growth due to the increasing demand for advanced, AI-based traffic solutions. This demand is driven by the escalating number of vehicles on the road and the resulting need for more efficient and effective traffic management systems. However, the market faces challenges as well. The lack of skilled professionals in government traffic organizations poses a significant barrier to the implementation and maintenance of these complex systems. Despite these challenges, the market presents numerous opportunities for companies seeking to capitalize on the growing demand for intelligent traffic management solutions.
Green traffic lights, on-demand transportation, and shared mobility services are also gaining popularity, contributing to the evolution of the traffic management infrastructure. Strategic partnerships, collaborations, and investments in research and development are key strategies for companies looking to stay competitive in this dynamic market. By addressing the skills gap and continuing to innovate, companies can help ensure the successful implementation and adoption of intelligent traffic management systems, ultimately improving traffic flow, reducing congestion, and enhancing public safety.

What will be the Size of the Intelligent Traffic Management Market during the forecast period?

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The market in the United States is experiencing significant growth, driven by the increasing demand for next-generation traffic management solutions. Traffic safety technologies, such as real-time traffic information, dynamic traffic routing, and pedestrian detection systems, are becoming essential components of the smart mobility ecosystem. The integration of traffic data acquisition and data-driven traffic management is revolutionizing urban traffic management, leading to road safety improvement and sustainable transportation. Traffic management innovation continues to shape the industry, with a focus on transportation network analysis, traffic data visualization, and traffic congestion mitigation.
Intelligent parking management and traffic incident detection are essential components of the market, ensuring efficient and safe traffic flow. The market is also witnessing the emergence of mobility-as-a-service (MaaS) platforms, which are transforming the way people move around cities. The market's growth is further fueled by the development of traffic management standards and the increasing adoption of data-driven approaches. The trend towards sustainable traffic management is also influencing the market, with a focus on reducing carbon emissions and improving overall transportation efficiency. In summary, the market in the United States is a dynamic and rapidly evolving industry, driven by the demand for next-generation traffic management solutions and the integration of data-driven approaches. The market's growth is underpinned by the need for improved traffic operations management, sustainable transportation, and the development of a smart mobility ecosystem.

How is the Intelligent Traffic Management Industry segmented?

The intelligent traffic management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Solution

  Traffic monitoring system
  Traffic signal control system
  Traffic enforcement camera
  Integrated corridor management
  Others


Component

  Surveillance cameras
  Video walls
  Traffic controllers and signals
  Others


End-user

  Government authorities
  Transport agencies
  Commercial


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America



  Middle East and Africa

By Solution Insights

The traffic monitoring system segment is estimated to witness significant growth during the forecast period. The market is witnessing significant advancements, particularly in the Traffic Monitoring Systems segment. By 2029, this segment is expected to evolve substantially, integrating advanced sensor technologies, video analytics, and real-time data processing frameworks. These systems will shift from reactive to proactive approaches, utilizing predictive analytics algorithms to anticipate congestion patterns and optimize signal timings dynamically. IoT-enabled devices and edge computing architectures will facilitate faster data transmission and localized decision-making, minimizing latency in traffic management operations. Furthermore, multimodal transportation data, including

Analysis of ‘Traffic Count Segments’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/d81619ba-78d6-4252-a540-b647adaf367a on 11 February 2022.

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

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 Taaffe

Contact E-Mail: sue_taaffe@tempe.gov

Contact Phone: 480-350-8663

Link to embedded web map:http://www.tempe.gov/city-hall/public-works/transportation/traffic-counts

Link to site containing historical traffic counts by node: https://gis.tempe.gov/trafficcounts/Folders/

Data Source: SQL Server/ArcGIS Server

Data Source Type: Geospatial

Preparation Method: N/A

Publish Frequency: As information changes

Publish Method: Automatic

Data Dictionary

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