Top Traffic Data APIs, Datasets, and Databases
Find the top commercial Traffic Data sets, feeds and streams.
Validate Traffic Volume Data
Russia+ 48 more
|Use Case||Location Intelligence, Location Analytics + 3 more|
INRIX Traffic Flow Incidents
|Use Case||Traffic Analysis|
INRIX Historical Traffic Information
|History||6 years of past data available|
|Use Case||Traffic Analysis|
Public Transport Database
|History||10 years of past data available|
|Use Case||Location Intelligence, Traffic Analysis + 3 more|
|Use Case||Store Visit Attribution|
INRIX Trips Reports
|History||6 years of past data available|
Russia+ 48 more
|Use Case||Trend Analysis, Traffic Analytics + 3 more|
Top Traffic Data Providers, Vendors, and Companies
Find the top Traffic Data aggregators, suppliers, and firms.
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The Ultimate Guide to Traffic Data 2020
Learn everything about Traffic Data. Understand data sources, popular use cases, and data quality.
Table of Contents
- What is Traffic Data?
- Who uses Traffic Data and for what use cases?
- What are typical Traffic Data attributes?
- How is Traffic Data typically collected?
- How to assess the quality of Traffic Data?
- How is Traffic Data typically priced?
- What are the common challenges when buying Traffic Data?
- What to ask Traffic Data providers?
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