At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.
What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.
How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.
Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:
Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.
Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.
Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.
In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.
HD Map For Autonomous Vehicles Market Size 2024-2028
The HD map for autonomous vehicles market size is forecast to increase by USD 14 billion at a CAGR of 40.5% between 2023 and 2029
The market is experiencing significant growth, driven by the increasing adoption of autonomous vehicles and the development of advanced connected infrastructure. The integration of high-definition maps into autonomous systems enables vehicles to navigate complex environments more accurately and efficiently, reducing the risk of accidents and improving overall performance. HD map creation for autonomous vehicles is a complex process involving data acquisition, aggregation, and integration of advanced technologies such as AI and machine learning. However, the high cost associated with the technology remains a significant challenge for market expansion. Manufacturers must continue to innovate and find cost-effective solutions to make HD maps an essential component of autonomous vehicles, rather than a luxury. Companies seeking to capitalize on this market opportunity should focus on collaborating with infrastructure providers, developing scalable and cost-effective HD mapping technologies, and ensuring seamless integration with autonomous systems. By addressing these challenges and leveraging the growing demand for autonomous vehicles and advanced infrastructure, market participants can effectively navigate the strategic landscape and drive long-term success.
What will be the Size of the Market during the forecast period?
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The market is experiencing significant growth as the global push towards advanced driver-assistance systems (ADAS) and fully autonomous vehicles (AVs) continues. HD Maps, which utilize technologies such as Lidar, SLAM (Simultaneous Localization and Mapping), and digital cameras, play a crucial role in enabling AVs to navigate roads safely and efficiently. These maps provide real-time, high-precision data to AV systems, allowing them to identify and respond to road conditions, obstacles, and other vehicles in real time. The market is expected to reach a substantial size in the coming years, driven by the increasing demand for shared mobility services, including ride-sharing and robo-taxi services.
The integration of 5G networks is also expected to accelerate the adoption of HD Maps, as they enable faster and more reliable data transmission between vehicles and maps. The market is witnessing continuous innovation, with companies investing heavily in research and development to improve the accuracy and coverage of HD Maps. Additionally, the integration of HD Maps with other technologies, such as sensor fusion and deep learning algorithms, is expected to further enhance the capabilities of AVs. Overall, the HD Map market for autonomous vehicles is a dynamic and rapidly evolving market, poised for significant growth in the coming years.
How is this Industry segmented?
The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Solution
Cloud-based
Embedded
Vehicle Type
Passenger
Commercial
Geography
North America
US
Europe
Germany
UK
APAC
China
Japan
Middle East and Africa
South America
By Solution Insights
The cloud-based segment is estimated to witness significant growth during the forecast period. HD maps are a critical component in the advancement of autonomous vehicles. These high-definition maps offer enhanced accuracy and precision for navigation, while their cloud-based infrastructure ensures accessibility and ease of updates. This enables autonomous vehicles to navigate complex and unfamiliar environments more effectively. Notable industry players, such as NavInfo Co. Ltd. (Navinfo), HERE Global BV (HERE), TomTom NV (TomTom), and NVIDIA Corp. (NVIDIA), prioritize cloud-based solutions and real-time services for their HD mapping offerings. The integration of 5G networks further enhances the capabilities of HD maps, contributing to the growth of autonomous driving technology in passenger and commercial vehicles.
Get a glance at the market report of share of various segments Request Free Sample
The cloud-based segment was valued at USD 1047.3 million in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
North America is estimated to contribute 40% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
For more insights on the market size of various regions, Request Free Sample
The market in North America is primarily driven by the United States, where the increasing deployment of
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Depicted on this map is British North America less than one hundred years after the fall of New France. It also shows the emergence of British influence prior to Confederation. British North America circa 1823 was comprised of Lower Canada, Upper Canada, New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland (including the Labrador Coast). The Northwest Territories were considered British possessions, while the Hudson’s Bay Company controlled Rupert’s Land. The United States and Britain jointly administered the Oregon Territory. This map along with New France circa 1740 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
Digital Map Market Size 2025-2029
The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.
The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.
What will be the Size of the Digital Map Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.
Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.
How is this Digital Map Industry segmented?
The digital map 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.
Application
Navigation
Geocoders
Others
Type
Outdoor
Indoor
Solution
Software
Services
Deployment
On-premises
Cloud
Geography
North America
US
Canada
Europe
France
Germany
UK
APAC
China
India
Indonesia
Japan
South Korea
Rest of World (ROW)
By Application Insights
The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.
Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance app
Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.
Information on the condition of roads in England, as well as other aspects of highways maintenance in the years to March 2020 and March 2021.
The data comes from multiple sources including National Highways (formerly Highways England) and local authorities. Some data from local authorities form part of the Single Data List, making the provision of data a mandatory requirement.
In the period ending March 2021, local authorities in England reported that:
were categorised as red (should have been considered for maintenance).
Of the roads managed by National Highways:
should have been considered for maintenance in period ending March 2021.
Local authorities provided data on a voluntary basis for their amber and green roads for the financial years ending 2020 and 2021. This information was published for ‘A’ roads for the first time in the 2019 release. Where local authorities have provided this information for 2019 to 2020 and 2020 to 2021, this has been included for ‘A’ roads alongside experimental statistics for ‘B’ and ‘C’ roads.
The statistical release does not present maintenance expenditure statistics for 2020 to 2021. This is because the source data for local roads had not been published at the point of production of this release. We are planning to publish an update of maintenance expenditure information alongside ‘Transport Statistics Great Britain 2021’.
Alongside these official statistics, new experimental statistics have also been published in ‘Experimental Statistics: Local Road Condition SCANNER data report, April 2017 to March 2021’, April 2017 to March 2021. This uses the underlying SCANNER data from local authorities to provide more granular analysis of road condition.
An new https://maps.dft.gov.uk/road-condition-explorer/index.html" class="govuk-link">interactive map has been published alongside this release. It presents information at road level on the condition of local authority managed classified (‘A’ roads, ‘B’ and ‘C’ roads), by condition category. This covers 2 time periods with data shown on the map for specific LAs, where this was available, in 2017 to 2019 and 2019 to 2021 respectively.
Road condition statistics
Email mailto:roadmaintenance.stats@dft.gov.uk">roadmaintenance.stats@dft.gov.uk
Media enquiries 0300 7777 878
ArcGIS Maritime server extension's Maritime Chart Service (MCS) capability is a Server Object Extension that provides both OGC WMS and Esri RESTful web services to quickly view and query your S-57 or S-63 encrypted datasets.The base data for this web service is sample AML data download from here. Datasets are not guaranteed to be kept up-to-date and are for demonstration purposes only. To learn more about this product visit ArcGIS Maritime.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Depicted on this map is the extent of New France at its territorial height circa 1740 prior to its great territorial losses to British North America. Also shown on the map are the territorial claims, administrative divisions, and the distribution of population and settlement (including fur trading posts) circa 1740. This map along with British North America circa 1823 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
Historical Map of South / Central America from the David Rumsey Historical Map Collection
The maps below show the population of the UK in 2022, at country, region, county and postcode sector level. The maps also provide information about the relative wealth, education and employment of people living in different areas.This map shows different countries of the UK.
📊 Google Data for Market Intelligence, Business Validation & Lead Enrichment Google Data is one of the most valuable sources of location-based business intelligence available today. At Canaria, we’ve built a robust, scalable system for extracting, enriching, and delivering verified business data from Google Maps—turning raw location profiles into high-resolution, actionable insights.
Our Google Maps Company Profile Data includes structured metadata on businesses across the U.S., such as company names, standardized addresses, geographic coordinates, phone numbers, websites, business categories, open hours, diversity and ownership tags, star ratings, and detailed review distributions. Whether you're modeling a market, identifying leads, enriching a CRM, or evaluating risk, our Google Data gives your team an accurate, up-to-date view of business activity at the local level.
This dataset is updated weekly, and is fully customizable—allowing you to pull exactly what you need, whether you're targeting a specific geography, industry segment, review range, or open-hour window.
🌎 What Makes Canaria’s Google Data Unique? • Location Precision – Every business record is enriched with latitude/longitude, ZIP code, and Google Plus Code to ensure exact geolocation • Reputation Signals – Review tags, star ratings, and review counts are included to allow brand sentiment scoring and risk monitoring • Diversity & Ownership Tags – Capture public-facing declarations such as “women-owned” or “Asian-owned” for DEI, ESG, and compliance applications • Contact Readiness – Clean, standardized phone numbers and domains help teams route leads to sales, support, or customer success • Operational Visibility – Up-to-date open hours, categories, and branch information help validate which locations are active and when
Our data is built to be matched, integrated, and analyzed—and is trusted by clients in financial services, go-to-market strategy, HR tech, and analytics platforms.
🧠 What This Google Data Solves Canaria Google Data answers critical operational, market, and GTM questions like:
• Which businesses are actively operating in my target region or category? • Which leads are real, verified, and tied to an actual physical branch? • How can I detect underperforming companies based on review sentiment? • Where should I expand, prospect, or invest based on geographic presence? • How can I enhance my CRM, enrichment model, or targeting strategy using location-based data?
✅ Key Use Cases for Google Maps Business Data Our clients leverage Google Data across a wide spectrum of industries and functions. Here are the top use cases:
🔍 Lead Scoring & Business Validation • Confirm the legitimacy and physical presence of potential customers, partners, or competitors using verified Google Data • Rank leads based on proximity, star ratings, review volume, or completeness of listing • Filter spammy or low-quality leads using negative review keywords and tag summaries • Validate ABM targets before outreach using enriched business details like phone, website, and hours
📍 Location Intelligence & Market Mapping • Visualize company distributions across geographies using Google Maps coordinates and ZIPs • Understand market saturation, density, and white space across business categories • Identify underserved ZIP codes or local business deserts • Track presence and expansion across regional clusters and industry corridors
⚠️ Company Risk & Brand Reputation Scoring • Monitor Google Maps reviews for sentiment signals such as “scam”, “spam”, “calls”, or service complaints • Detect risk-prone or underperforming locations using star rating distributions and review counts • Evaluate consistency of open hours, contact numbers, and categories for signs of listing accuracy or abandonment • Integrate risk flags into investment models, KYC/KYB platforms, or internal alerting systems
🗃️ CRM & RevOps Enrichment • Enrich CRM or lead databases with phone numbers, web domains, physical addresses, and geolocation from Google Data • Use business category classification for segmentation and routing • Detect duplicates or outdated data by matching your records with the most current Google listing • Enable advanced workflows like field-based rep routing, localized campaign assignment, or automated ABM triggers
📈 Business Intelligence & Strategic Planning • Build dashboards powered by Google Maps data, including business counts, category distributions, and review activity • Overlay business presence with population, workforce, or customer base for location planning • Benchmark performance across cities, regions, or market verticals • Track mobility and change by comparing past and current Google Maps metadata
💼 DEI, ESG & Ownership Profiling • Identify minority-owned, women-owned, or other diversity-flagged companies using Google Data ownership attributes • Build datasets aligned with supplier diversity mandates or ESG investment strategies • Segment location insi...
Crop year 2014 US map at the county level shows designations across the country under USDA's amended rule. The faster, more efficient process will immediately expand assistance to more than 1,000 counties in 26 states.
Geologic Map of North America (Southern Sheet). Map published by Geological Society of America; database by U.S. Geological Survey. See Catalogue of Registered Services for more information.
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
National Library of Scotland Historic Maps APIHistorical Maps of Great Britain for use in mashups and ArcGIS Onlinehttps://nls.tileserver.com/https://maps.nls.uk/projects/api/index.htmlThis seamless historic map can be:embedded in your own websiteused for research purposesused as a backdrop for your own markers or geographic dataused to create derivative work (such as OpenStreetMap) from it.The mapping is based on out-of-copyright Ordnance Survey maps, dating from the 1920s to the 1940s.The map can be directly opened in a web browser by opening the Internet address: https://nls.tileserver.com/The map is ready for natural zooming and panning with finger pinching and dragging.How to embed the historic map in your websiteThe easiest way of embedding the historical map in your website is to copy < paste this HTML code into your website page. Simple embedding (try: hello.html):You can automatically position the historic map to open at a particular place or postal address by appending the name as a "q" parameter - for example: ?q=edinburgh Embedding with a zoom to a place (try: placename.html):You can automatically position the historic map to open at particular latitude and longitude coordinates: ?lat=51.5&lng=0&zoom=11. There are many ways of obtaining geographic coordinates. Embedding with a zoom to coordinates (try: coordinates.html):The map can also automatically detect the geographic location of the visitor to display the place where you are right now, with ?q=auto Embedding with a zoom to coordinates (try: auto.html):How to use the map in a mashupThe historic map can be used as a background map for your own data. You can place markers on top of it, or implement any functionality you want. We have prepared a simple to use JavaScript API to access to map from the popular APIs like Google Maps API, Microsoft Bing SDK or open-source OpenLayers or KHTML. To use our map in your mashups based on these tools you should include our API in your webpage: ... ...
Overview
Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.
Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.
The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.
Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)
In-depth spatial analysis
Clustering
Geofencing
Reverse Geocoding
Reporting and Business Intelligence (BI)
Product Features
Coherence and precision at every level
Edge-matched polygons
High-precision shapes for spatial analysis
Fast-loading polygons for reporting and BI
Multi-language support
For additional insights, you can combine the map data with:
Population data: Historical and future trends
UNLOCODE and IATA codes
Time zones and Daylight Saving Time (DST)
Data export methodology
Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson
All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why companies choose our map data
Precision at every level
Coverage of difficult geographies
No gaps, nor overlaps
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United Kingdom Exports to United States was US$71.77 Billion during 2024, according to the United Nations COMTRADE database on international trade. United Kingdom Exports to United States - data, historical chart and statistics - was last updated on July of 2025.
Unlock precise, high-quality Map data covering 164M+ verified locations across 220+ countries. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.
Key use cases of GIS Data helping our customers :
Environmental Sensitivity Index (ESI) maps are an integral component in oil-spill contingency planning and assessment. They serve as a source of information in the event of an oil spill incident. ESI maps contain three types of information: shoreline habitats (classified according to their sensitivity to oiling), sensitive biological resources, and human-use resources. Most often, this information is plotted on 7.5 minute USGS quadrangles, although in the Alaska ESI maps, USGS topographic maps at scales of 1:63,360 and 1:250,000 are used, and in other ESI maps, NOAA charts have been used as the base map. Collections of these maps, grouped by state or a logical geographic area, are published as ESI atlases. Digital data have been published for most of the U.S. shoreline, including Alaska, Hawaii, and Puerto Rico.
Click here to open the ArcGIS Online 3D Map Viewer and work through the examples shown belowTo add 3D data to ArcGIS Online you will need a login for an ArcGIS Online account. We would recommend that you use a free schools subscription (full functionality) or the free public account (reduced functionality).Login to ArcGIS OnlineFind Mount Everest and save the 3D map so that it opens with an amazing view of the mountainShare your 3D map with a friend or colleague and get some feed back
A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Global Zip Code Database (Market Research data)
Address capture and validation
Map and visualization
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Data export methodology
Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Fully and accurately geocoded
Administrative areas with a level range of 0-4
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes
Time zones and Daylight Saving Times
Why do companies choose our Market Research databases
Enterprise-grade service
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.
At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.
What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.
How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.
Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:
Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.
Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.
Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.
In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.