Traffic Analysis Aerial View

## Overview

Traffic Analysis Aerial View is a dataset for object detection tasks - it contains Cars Trucks Buses Cycles annotations for 2,757 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

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.

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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

Network Traffic Analysis Market is Segmented by Deployment (On-Premise, Cloud-Based, and Hybrid), Component (Solutions and Services), Organization Size (Large Enterprises and Small and Medium Enterprises), End-User Industry (BFSI, IT and Telecom, and More), and Geography. The Market Sizes and Forecasts are Provided in Value (in USD Million) for all the Above Segments.

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.

similarweb.com is ranked #1119 in IN with 18.51M Traffic. Categories: Information Technology, Online Services. Learn more about website traffic, market share, and more!

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.

Top View Traffic

## Overview

Top View Traffic is a dataset for object detection tasks - it contains Vehicles annotations for 9,870 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Traffic Sign Update

## Overview

Traffic Sign Update is a dataset for object detection tasks - it contains Traffic Sign Update annotations for 326 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset contains traffic incident information from the Austin-Travis County traffic reports collected from the various Public Safety agencies through a data feed from the Combined Transportation, Emergency, and Communications Center (CTECC).

For further context, see: - Active Incidents: Map and Context - https://data.austintexas.gov/stories/s/Austin-Travis-County-Traffic-Report-Page/9qfg-4swh/ - Data Trends and Analysis - https://data.austintexas.gov/stories/s/48n7-m3me

The dataset is updated every 5 minutes with the latest snapshot of active traffic incidents.

ahrefs.com is ranked #2600 in US with 24.1M Traffic. Categories: Advertising and Marketing, Computer Software and Development, Online Services. Learn more about website traffic, market share, and more!

This is 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. Historical traffic is based on the average of observed speeds over the past three years. 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 image can be requested for the current time and any time in the future. A map image for a future request might be used for planning purposes. The map layer 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.

From October 2024 to February 2025, ChatGPT outperformed competing AI-powered search engines in traffic referral, achieving a total growth of 155.52 percent. Perplexity placed second, despite experiencing more significant fluctuations, with a total growth of 54.78 percent by the conclusion of the analyzed period. With a 43.64 percent overall growth, Google's Gemini ranked third among other engines and maintained the most consistent traffic referral rate. Artificial intelligence-driven trends, notably AI-powered search, are changing online traffic patterns. This suggests a more significant change in the way users find information online and is expected to have a knock-on effect on the digital advertising sector.

The urban and rural traffic counting programme is monitored by a network of traffic stations in the four major urban centres (Darwin, Katherine, Tennant Creek & Alice Springs), and in all rural areas throughout the Northern Territory. The traffic counting stations are divided into the categories of Primary, Coverage and Special.

Contextual explainer page for the Austin-Travis County Traffic Report page

Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Click enhances the unparalleled accuracy of CE Transact by allowing investors to delve deeper and browse further into global online web traffic for CE Transact companies and more. Leverage the unique fusion of web traffic and transaction datasets to understand the addressable market and understand spending behavior on consumer and B2B websites. See the impact of changes in marketing spend, search engine algorithms, and social media awareness on visits to a merchant’s website, and discover the extent to which product mix and pricing drive or hinder visits and dwell time. Plus, Click uncovers a more global view of traffic trends in geographies not covered by Transact. Doubleclick into better forecasting, with Click.

Consumer Edge’s Click is available in machine-readable file delivery and enables: • Comprehensive Global Coverage: Insights across 620+ brands and 59 countries, including key markets in the US, Europe, Asia, and Latin America. • Integrated Data Ecosystem: Click seamlessly maps web traffic data to CE entities and stock tickers, enabling a unified view across various business intelligence tools. • Near Real-Time Insights: Daily data delivery with a 5-day lag ensures timely, actionable insights for agile decision-making. • Enhanced Forecasting Capabilities: Combining web traffic indicators with transaction data helps identify patterns and predict revenue performance.

Use Case: Analyze Year Over Year Growth Rate by Region

Problem A public investor wants to understand how a company’s year-over-year growth differs by region.

Solution The firm leveraged Consumer Edge Click data to: • Gain visibility into key metrics like views, bounce rate, visits, and addressable spend • Analyze year-over-year growth rates for a time period • Breakout data by geographic region to see growth trends

Metrics Include: • Spend • Items • Volume • Transactions • Price Per Volume

Inquire about a Click subscription to perform more complex, near real-time analyses on public tickers and private brands as well as for industries beyond CPG like: • Monitor web traffic as a leading indicator of stock performance and consumer demand • Analyze customer interest and sentiment at the brand and sub-brand levels

Consumer Edge offers a variety of datasets covering the US, Europe (UK, Austria, France, Germany, Italy, Spain), and across the globe, with subscription options serving a wide range of business needs.

Consumer Edge is the Leader in Data-Driven Insights Focused on the Global Consumer

Hourly traffic live index for selected cities, including Riyadh, Dubai, Doha, Kuwait, and Cairo from December 16, 2022 till January 4, 2023. Data is collected from tomtom - traffic reports.

Non-commercial use only.

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

According to the results of a survey conducted worldwide in 2023, nearly **** of responding digital marketers believed artificial intelligence (AI) would have a positive impact on website search traffic in the next five years. Some ** percent stated AI would have a neutral effect, while ** percent agreed that the technology would negatively impact search traffic.