ITS Australia member Intelematics has been in the business of data for over 20 years. As a society, the collection and application of data have improved astronomically in that time. We’ve seen the emergence of Big Data, the Internet of Things, Artificial Intelligence (AI) and Machine Learning. As the world moved through this digital and data transformation, Intelematics consistently capitalised on new data capabilities to become the main provider of real-time traffic information for over 75% of the Australian auto-manufacturing market.
However, in the last six months, the world has changed in more ways than one. And these changes have forced governments, businesses and individuals to take stock of their reality, reflect and rethink the way forward.
Intelematics has been closely tracking road traffic for years and continued to do so through the pandemic. We have always strived towards providing different stakeholders with a single source of truth, and the right set of tools for informed decision making.
The birth of SUNA: Australia’s real-time traffic staple for twelve years and counting
Data has always been at the core of Intelematics as a business. Before we talk about the present and future of our data capabilities, it is important to acknowledge the past.
I’d like to take you back to 2008 – the beginning of our mobility data journey. In that year, we introduced Australia and New Zealand to SUNA Live Traffic (SUNA). SUNA was our first foray into harnessing mobility data to improve the efficiency of our road networks.
SUNA is a comprehensive real-time satellite traffic information service that provides live traffic updates directly to in-vehicle and compatible GPS devices.
SUNA collects real-time data on live incidents, traffic flow and congestion levels. That data is then processed by Intelematics and communicated to drivers’ on their in-vehicle navigation devices. When SUNA first launched, this data was only transmitted through FM radio broadcast. Nowadays, while data captured through SUNA is still transmitted through FM radio broadcast, it is also communicated through mobile data.
SUNA has been keeping Australians and New Zealanders moving for the last 12 years. SUNA is currently licensed by 75% of the Australian vehicle manufacturing market and covers 90% of traffic across Australia and New Zealand.
This means that for more than a decade, we have collected a bank of historical mobility data. Slowly but surely, we have been building a comprehensive view of the Australian and New Zealand road and traffic network. In the process, we have identified the impact certain conditions have on traffic and traffic trends over the years.
Having recorded over 200,000 incidents to date, we specialise in historical and real-time traffic data for speed, congestion, volume and incidents. Our road traffic data is collected through thousands of probes and sensors located on roads, in vehicles and infrastructure with collections as rapid as per second frequencies. We enrich our data using multiple proprietary sources and machine taught algorithms.
When it comes to SUNA itself, the data communicated through the channel is only valid and useful if it’s live. Once the data became dated (or historical), it lived in our system – unused.
This is when we started having conversations internally about how we could harness our historical traffic data to derive insights that would offer more value, not just for our end users – the vehicle manufacturers and their customers – but the wider public, policymakers, engineers and urban planners in designing a more robust, intuitive and futuristic road network.
INSIGHT’s inception was the answer. Its purpose is to ensure we can look into the past and draw meaningful insights to ensure we build a better future. Providing every stakeholder with the ability to use insights powered by Big Data, Artificial Intelligence and Machine Learning and get a peek into what the future might look like.
Data evolution – INSIGHT: The first historical mobility datastore
As a first step, we set about adding structure to the massive amounts of historical data we had collected for more than a decade. To do this, we began sorting the data by flow (average speeds), volume (average vehicle count), and origin and destination.
Then we grouped the data by time (year, month, day, hour, minute, time intervals) and location (local government area, suburb, street name, road sections, unique IDs). We then went about turning the historical data into easily downloadable files that had been transformed into a structured, easy-to-interpret format.
Through our research, we discovered that the types of people looking for comprehensive mobility data typically included, local councils, traffic and transport engineers, infrastructure planners, urban designers and construction companies. They needed this data to assess the site and land-use locations to demonstrate the viability of their plans to their teams, boards or local constituents.
We found that there was a need for quality, high-resolution traffic data and insights. Why? Because there was a strong pipeline of national projects and these projects were relying on difficult to decipher, open-source data which differed by state and was rarely kept up to date. Therefore, a lot of analysis and preparation work would be required to transform the data into a format that could be easily understood by a construction company’s board or management team, or a local council.
The industry was lacking a centralised data source that provided mobility data for the whole country. We sought to rectify this problem. We wanted to give them a one-stop-shop for all their mobility data needs. Our goal was not only to harmonise the data but also to make it as user-friendly as possible.
Our first iteration of INSIGHT was – a data store. At the beginning of2020, we released traffic flow data files for over 2,000 Australian suburbs and made them available for online purchase. The files provide average travel speeds for any given location at any given time of day in an easy-to-interpret .csv file. The files were available for once-off purchase based on the location and timeframe customers were searching for.