Photograph taken from above of New York City

Meet Return on Traffic Data

The new potential for contextualized transportation analytics

Abstract image showing blue, white and yellow lights

Chapter 1

The state of transportation data today

Intelligent transportation systems are changing in a big way. You’ve felt it.

Population densities are shifting as people leave mega-urban centers.

Commercial delivery models are evolving as goods are increasingly delivered door-to-door.

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?

Chapter 2

The next evolutionary step

Commercial and consumer transportation insight is essential to city planning.

It tells us how to develop our infrastructure, create policy and run economic initiatives – often at a huge scale. But here’s the thing.

We’ve always been limited by the insights at our disposal.

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.

Closeup photograph of raindrops on a car's windshield

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.

At the same time, the potential for aggregated transportation insights has gone up exponentially.

There’s an ever-growing ocean of these insights.

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.

Aerial photograph of a large number of cars in a parking lot

Chapter 3

Unlocking the new potential

Today, we have the technology necessary to process and aggregate massive volumes of connected-vehicle data.

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

Abstract image of a black hexagonal mesh pattern

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.

Photograph of a courier lifting a parcel out of a van

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.

Chapter 4

The power of Return on Traffic Data

When you combine trip context and volume, incredible things happen.

Traffic engineers and transportation planners can make more informed traffic management and planning decisions, faster across entire regions or within a single city block.

It’s what we call Return on Traffic Data:

Actual, tangible business value that manifests as proactive and predictive citywide action.

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.

See our solutions

Aerial photograph of traffic at a crossing in Marunouchi, Tokyo

Chapter 5

Meet Geotab Altitude

We’re Geotab Intelligent Transportation Systems. We’ve built our Altitude platform to unify trip context and volume to produce industry leading transportation insights.

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.

Aerial photograph of traffic at a highway crossing over a river in Amsterdam, Netherlands

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.

Contextualized transportation analytics are helping DOTs build a more holistic view of local and regional road usage.

And that makes the previously impossible possible. Ready to get started?

Learn more about Altitude Talk to us