Meet Return on Traffic Data
The new potential for contextualized transportation analytics
The state of transportation data today
We’ve arrived at an inflection point – one where DOTs can access a depth and breadth of hyper-relevant insights that were previously hidden.
Insights that can support the development of safer, more efficient and more sustainable cities.
And that’s good news for people with even a passing interest in the potential of transportation-derived action (and that’s pretty much everyone).
Because by riding this change, we can make cities, municipalities – even entire regions – better places to live, work and travel.
The question is – how do we get there?
The next evolutionary step
Traditional data capture practices, like mail-in surveys, offer detailed trip context but lacked the necessary volume due to low response rates.
As technologies evolved, automated vehicle detection equipment solved this problem…
…but at the cost of understanding the granular context behind the metrics they produce.
This makes it difficult to understand the contributing factors to road usage and explain spot patterns and traffic anomalies. And that forces us to be reactive.
Traditional transportation data and models allow us to solve transportation problems, but typically after the fact.
You notice an issue (the where and when). And you solve it. But what’s often hidden is the why. The root cause is less obvious than the problem it creates. We’re still left to answer questions of wider context, like…
What’s the primary purpose of the trips on my road?
What’s being moved, people or goods, and how does that change per hour of day?
Why was a particular route taken?
What vehicle class was used?
Today, as transportation networks between and within cities grow and evolve (often at incredible speed), we’re reacting to more new issues, more often.
And while we’re already deriving masses of value from this ocean, there’s now the potential to do more.
To proactively take on new transportation challenges and quickly root out blockers to better city living.
And it starts by marrying context and volume.
Unlocking the new potential
If this all sounds a little too good to be true, that’s because, until recently, it was.
Then the Internet of Things happened.
This changed what’s possible for vehicle telemetry and analytics.
Not just in how we obtain data…
…but also in how we understand and use it to produce macro and micro transportation analytics
When combined with leading data science and AI practices, connected-vehicle data can be transformed into contextual people and goods movement insights used to understand the ‘why’ behind our transportation networks.
And that’s the heart of this new potential – we can quickly identify and resolve mobility challenges proactively.
DOTs can get the context they need to find the root causes of problems, understand why they’re happening and craft solutions that fix the long term and more immediate problems.
And once we understand the cause, we can better predict issues in advance and find solutions to them before they occur.
Let’s see how this looks in practice.
The power of Return on Traffic Data
Just a few use cases include…
Stop and Parking analysis:
- Where are trucks are parking along highway networks, how long trucks are parked for and at what times of days?
- How to appropriately plan for these stops when taking into consideration things like curbside management and corridor electrification?
- What impact does parking activity have on curbside usage and how can that analysis be used to build efficient curbside usage programs for city, state, and overall infrastructure planning?
Origin & Destination:
- What is the true origin and destination of a trip, independent of small detours and stops along the way?
- What are the predominant routes taken between Origin and Destination hotspots?
- What commercial industries do these major commercial hubs and throughways service?
- What is the primary purpose of the trips on our roads?
Road & traffic engineering:
- How are different vehicle classes affecting corridor synchronization efficiencies and level of service?
- How will an explosion of commercial door-to-door deliveries affect your curbside management plans?
- Does the existing network support the efficient movement of goods and services in the industries you’re trying to support?
- How are vehicles reacting to and rerouting around local anomalies and disturbances?
Contextualized transportation insights helps us answer these questions.
And by uncovering these blind spots, we can proactively manage the vehicular demands and behaviors creating the issues in front of us.
Meet Geotab Altitude
Altitude processes billions of data points per day from different sources of commercial and consumer vehicle data to generate transportation intelligence for better, faster decision-making.
And it does this to help progressive DOTs modernize processes and increase operational efficiency and safety.
Here’s what it can do for you:
Analyze growing last mile and curbside delivery activity in your downtown.
Identify and remove pivotal factors behind inefficient traffic flow and road accidents.
Plot true journey origins and destinations and provide context to the trip volumes on your roads.
Uncover speed and travel time insight broken down by vehicle class and trip purpose.
Do all of this through a simple click and drag UI and APIs capable of quickly generating the kinds of transportation insights you require.