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Traffic Data

Traffic data refers to information about the geographical movement of vehicles. It's mostly used by governments and logistics companies e.g. in city urban planning and route planning. Datarade helps you find the right traffic data providers and datasets.

Top Traffic Data APIs, Datasets, and Databases

Find the top commercial Traffic Data sets, feeds and streams.

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Validate Traffic Volume Data

by DDS Digital Data Services
Validate is one of the largest traffic models in the world. It supplies car and truck volumes for Germany's entire major road network. The traffic data from Validate can be used for site analysis a...
Volume5.5M records
Country
Germany
France
Russia
+ 48 more
Use CaseLocation Intelligence, Location Analytics + 3 more
Available Pricing:
One-off purchase
Yearly subscription
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INRIX Traffic Flow Incidents

by INRIX
INRIX Traffic Flow Incidents are algorithmically generated events based on INRIX real-time flow data.
Use CaseTraffic Analysis
Available Pricing:
Monthly subscription
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INRIX Historical Traffic Information

by INRIX
A comprehensive collection of historic speed and travel time data to help analyze how traffic responded to a specific moment in time or typically flows on a particular roadway segment.
History6 years of past data available
Use CaseTraffic Analysis
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Public Transport Database

by Wikiroutes
Public transport content in different formats, which includes flexible adapters for local data formats: * Routes * Trips * Shapes * Stops * Stations (Entrances/Exits/Platforms) * Icons and c...
History10 years of past data available
Use CaseLocation Intelligence, Traffic Analysis + 3 more
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Usage Based
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Patterns

by SafeGraph
Place traffic and demographic aggregations that answer: how often people visit, where they came from, where else they go, and more. Available for ~3.6MM POI.
Use CaseStore Visit Attribution
Pricing available upon request
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INRIX Trips Reports

by INRIX
INRIX Trips Report provides travel path data related to the start, end, and waypoints of trips to, from, through, and within user defined zones or corridors.
History6 years of past data available
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Work-Route Matrix

by DDS Digital Data Services
Not only are the daytime and night-time populations of interest for location planning. Commuter flows also have a great significance. They can be used to identify certain routes as lucrative areas ...
Country
Germany
France
Russia
+ 48 more
Use CaseTrend Analysis, Traffic Analytics + 3 more
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Top Traffic Data Providers, Vendors, and Companies

Find the top Traffic Data aggregators, suppliers, and firms.

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Based in United States of America

INRIX is the global leader in connected car services and transportation analytics. Leveraging big data and the cloud, INRIX delivers comprehensive services and solutions to help move people, cities...

Based in Switzerland

The better we understand the way we move, the better we can build cities, mobility services and transportation systems to meet our needs. Teralytics offers the most advanced insights on human mo...

Based in United States of America

StreetLight Data pioneered the use of Big Data data analytics to help data experts solve their biggest problems. Applying proprietary machine-learning algorithms to over ~40 billion anonymized loca...

Based in Russian Federation

WikiRoutes is a Public Transit Platform that provides data worldwide. Database contains key information for ITS (Route and stops attribution, Transport types, Time Schedule, Public transport fea...

Based in United States of America

Here is a data provider offering Electric Vehicle Charging Stations Data, Traffic Data, Parking Availability Data, Location Data, Map Data, Cell Tower Data, Building Footprint Data, and Point of In...

Based in Netherlands

TomTom is a data provider offering Location Data, Map Data, and Traffic Data. They are headquartered in Netherlands. TomTom offers datasets in countries such as Germany and Spain.

Based in United Kingdom

ITO World is a data provider offering Traffic Data. They are headquartered in United Kingdom.

Based in United States of America

Waze is a data provider offering Location Data, Traffic Data, Satellite Data, and Map Data. They are headquartered in United States of America.

Based in Canada

INRIX ParkMe is a data provider offering Vehicle Location, Parking Availability Data, Traffic Data, and Satellite Data. They are headquartered in Canada.

Based in United States of America

Uber Movement is a data provider offering Location Data and Traffic Data. They are headquartered in United States of America. Uber Movement offers datasets in countries such as Australia and Belgium.

The Ultimate Guide to Traffic Data 2020

Learn everything about Traffic Data. Understand data sources, popular use cases, and data quality.

What is Traffic Data?

When we speak of Traffic Data, we refer to the data that measures and counts the flow of traffic. As traffic gets worse in cities, Traffic Data analytics improves the situation today, and helps plan for the future. Traffic is the cornerstone of modern economies. Traffic Data can be used for a variety of different purposes, from speed fining to urban planning. Traffic Data maps give an accurate understanding of traffic volume and movement patterns in a given area. This can be essential to businesses, in areas such as planning where to locate new premises. Retailers may want to locate in areas that have a high volume of traffic. Tourist premises may want to ensure a natural attraction draws adequate traffic to warrant locating at the site. Smart AI’s and Deep Learning are the leading-edge methods used for traffic related predictions.

Traffic Data is a major driver in many industries. One of the most important aspects of Traffic Data is how it can be integrated into many separate systems to yield various results. For instance, a retailer might want to use a Traffic Data map to plan the optimum site for a new premises. Whereas a health authority might want to utilise Traffic Data to plan the quickest route for their ambulances in an emergency.

At the moment, more Traffic Data is available than ever before. More and more businesses will start to utilize Traffic Data and, more specifically, will choose to combine their internal datasets with those of external for their mutual benefit. As systems grow ever more sophisticated and continue to be integrated into a growing number of business technologies, Traffic Data will increase in vital significance in providing better insights for planning and management. Businesses will be able to organise, store, interpret and share Traffic Data and other types of data to improve their businesses.

Who uses Traffic Data and for what use cases?

Multiple Data Traffic models and analysis and prediction methods have been developed to meet the needs of businesses. The last few years have seen an increasing surge in new technological advances. These new technologies have penetrated every level of everyday life and give rise to smart infrastructure developments. Smart Transportation infrastructure is at the leading-edge of these developments. Traffic Data can be used for traffic analysis, urban planning, route planning and other uses. Traffic Data can be used by local authorities for road maintenance planning; as well as providing the general public with access to data about levels of traffic in and around their local area. Retailers and petrol stations also use Traffic Data when planning the location of their services.

By counting pedestrians and cyclists, decision makers can determine trends in trail and facility usage. This foot traffic data can be used to inform planning and maintenance. Understanding peak usage trends determines if a trail or facility is primarily being used for recreational, utilitarian or commuting purposes. With Traffic Data software users can perform powerful analyses with just a few clicks. Companies can ask their data provider organise and personalise Traffic Datasets to suit their personal needs. Traffic Data can be tracked yearly or used to identify monthly, weekly, even daily trends.

Realtime displays are ideal for promotions, communicating progress and engaging in dialogue. Statistical methods, AI’s, Deep Learning and data mining techniques are increasingly being utilised to analyse Traffic Data. Deep Learning allows predictions of future road traffic characteristics. The use of Deep Learning is still in its infancy, and presently limited in scope compared to the Traffic Data collected by transportation authorities, but this is an area set to grow. In time it will produce in-depth analysis through connected networks. This will transform Traffic Data predictions as we know it and lead to new emerging businesses.
At the moment, a new project is in progress which aims to use wireless communication sensors, smart materials and energy generation and storage to create smart roads that generate electricity from passing traffic using smart infrastructure. The electricity harvested will be stored in roadside batteries and used to power street lamps, road signs or air pollution monitors, as well as sensors that can sense when potholes are forming. The smart roads will also collect data on traffic speeds, the types of vehicles that travel the road and other information on traffic flows. This data will help local authorities to better manage traffic flow. The possibilities for innovations powered by new smart technologies are endless.

This is only one of many emerging projects planning to use new smart data in innovative ways. In Bergen, Norway, the world’s first autonomous light rail system has been developed. It will reduce costs, as there is no driver to pay. It may also improve punctuality and reliability and increase customer satisfaction.

What are typical Traffic Data attributes?

Typical attributes of Traffic Data include: vehicle counts measuring the flow of traffic, speed counts to measure average speed, occupancy counts to measure how long vehicles occupied a given area.

The forecasting or prediction of Traffic Data characteristics allow insights that facilitate planning, modifications, or development. Traffic data attributes may be used in planning new road networks and developing traffic control strategies. Real-time Traffic Data predictions allows control of road traffic with traffic signals, variable lane control, variable message signs and other methods. Simulations and models can be created from predictions to help with traffic management and road congestion.

How is Traffic Data typically collected?

Many forms of data can be collected including traffic volumes, queue length assessments, saturation flow, travel speeds, vehicle classification, origins, destinations, journey times, pedestrian bicycle volumes, plus more. Traffic Data is collected in numerous ways: by manual turning counts such as surveys which measure traffic flow and delays. Parking surveys identifies issues and restraints and suggest measures to for meeting parking demands. Pedestrian surveys measure the flow of pedestrians at junctions and suggests improvements for the safe movement of foot traffic. Cameras are employed for number plate recognition. Placement of automatic traffic recorders and intelligent traffic cameras allows important Traffic Data to be collected. Manual review of historic published data and in-person surveys are also employed for collection purposes. Traffic Data is stored in files and on a Zoom 7 tile large enough to cover a major metropolitan area or small European country.

Traffic count data can be retrieved by Bluetooth connected to a counter and data can be retrieved up to six metres away from the counter. Traffic Data can be automatically wirelessly downloaded by GSM/4G transmission. This allows daily transmission of Traffic Data. Count data is automatically stored in software where it is available for analysis. Real-time count data can also be accessed through an Ethernet/ IP connection. Other methods of collection include: GPS devices and mobile signals to collect vehicle location and congestion data. Also, big data and high performance computing technologies, mobile, fog and cloud computing technologies, image processing, AI’s, urban logistics, vehicular ad hoc networks, autonomous driving, autonomic transportation systems, traffic event detection on social media, plus more.

How to assess the quality of Traffic Data?

High quality Traffic Data is essential to obtain accurate reports. Data needs to be consistent and up-to-date. There are steps users can take to assess the quality of their Traffic Data:

  • Buying from a reputable source with excellent reviews is one way of ensuring quality.
  • Regular checks with your own error detection systems should also be employed.
  • Regular testing and assessment is the best way to ensure quality Traffic Data. These checks can be set up to run automatically.

How is Traffic Data typically priced?

Prices for Traffic data depends on many variables and suppliers typically have several pricing models in place. Prices will depend on what the Traffic Data is to be used for, how many people in your company need access to the Traffic Data, and the geographical areas required for Traffic Data analysis.

What are the common challenges when buying Traffic Data?

Common challenges include ensuring Traffic Data is up-to-date. It is also necessary to ensure the Traffic Data collected matches your company’s needs. This entails analysing raw data and setting parameters to customise to your company’s needs. Extraction of useful information is a complicated process and requires in-depth understanding of the in-put database attributes. Trial and error with different questions is the best way to get useful results.

Businesses need to keep abreast of compliance regulations and new Traffic Data techniques. Companies also need to ensure their staff is trained in using Traffic Data effectively.

Businesses need to ensure Traffic data is tested regularly for accuracy and error minimisation.

What to ask Traffic Data providers?

  • How often is the Traffic Dataset updated?
  • Does the Traffic Data analytics system use Machine Learning techniques to improve performance over time?
  • Will the Traffic data system integrate with my existing business technologies?

Categories Related to Traffic Data

Explore similar categories related to Traffic Data.

Popular Traffic Data Use Cases

Find out the most common applications of Traffic Data.

Traffic Analysis Supply Chain Intelligence Traffic Analytics Autonomous Driving