Note: Since publishing this blog post, we have renamed the Congestion Analysis to "Traffic Diagnostics."
“Big Data” is becoming buzzier and buzzier, but the adage “data is just a cost until you use it” is an increasingly common refrain. As the CEO of a transportation analytics company, I’m a true believer in the power of data. It frankly makes me sad to see so many groups investing in the idea of Big Data only to feel disappointed when they can’t get any useful information out of it. At StreetLight Data, our top priority is to help the transportation industry “put Big Data to work”.
That’s why I’m thrilled to announce the latest feature for StreetLight InSight (that’s our on-demand platform for turning mobile device data into actionable transportation analytics.) It’s called the Congestion Analysis, and it’s designed to help you put Big Data to work to solve traffic jams. Lots of tools (including your eyes!) can tell you where traffic jams are occurring. The Congestion Analysis can tell you why the jam occurs, and suggests data-driven ideas for the best long-term solutions.
The Congestion Analysis is very different from every other feature that we’ve introduced to StreetLight InSight because – and this may surprise you – all of the analytics it provides were already available in our platform. The change is how we weave the Metrics together to tell a story, making StreetLight InSight Metrics much easier to use for congestion busting in the real world of transportation planning, modeling, and engineering.
Diagnosing Traffic Jams
There are a ton of tools out there for identifying where traffic jams are occurring. The Congestion Analysis is different: It helps transportation planners quickly diagnose the causes of traffic jams and identify the highest potential mitigation and demand management tactics. It uses different types of StreetLight InSight Metrics derived from navigation-GPS data, location-based services data, and contextual data sets in combination. Under the hood, the Congestion Analysis pulls together and organizes a suite of different StreetLight InSight analytics so that you can better understand and address traffic jams. These analytics include:
- Origin-Destination to Preset Geography – Transportation Analysis Zones (TAZs)
- Zone Activity Analysis
- 2016 AADT (Beta)
- Premium Trip Attributes
- Premium Traveler Attributes
Previously, StreetLight InSight users could run all of these Metrics separately, then combine them using MS Excel or other analysis tools to understand specific traffic jams. However, that could get time-consuming, especially for complex congestion issues. We wanted to make the process more straight-forward and easy, particularly for non-technical users of StreetLight InSight.
Congestion Busting Storytelling
Let’s face it: There’s only so much you can do with a .CSV file. If you really want to understand row upon row of data points, you must transform the data into graphical representations like charts, graphs, and heat maps. That’s why the Congestion Analysis lets you explore the analytics with our new interactive visualization tool. I think these visualizations are the key to slicing and dicing Big Data into actionable information.
Check out this quick 2-minute video for an example of storytelling with our new interactive visualization tool and the Congestion Analysis:
As you can see, the Congestion Analysis helps transportation planners use Big Data to “tell a story” about traffic jams – and that story concludes with concrete, real-world actions that can help address congestion. Thanks to our new interactive visualization tool, it is quick and easy to identify the characteristics and probable causes of traffic jams -- all without downloading a single. CSV. But don’t worry! Those .CSVs are still available to download. We hope (and anticipate) that our clients will use the interactive visualizations in our Congestion Analysis as a jumping-off point for deeper statistical analysis and modeling.
Congestion Problem Solving with Big Data
If you watched the video above, you saw that our Congestion Analysis does one key thing that’s completely brand-new for StreetLight InSight: It proposes potential solutions to a transportation challenge. For those that skipped the video, here’s a screenshot:
As you can see, StreetLight InSight is presenting the mitigation and demand management tactics that the data indicate are the best solutions for a particular jam. But this is not a robot that tells you exactly what to do. The Congestion Analysis doesn’t understand political context. It doesn’t know what areas will be more or less expensive to renovate, and it hasn’t heard the unique concerns of your constituents. The idea is to help you rank the top priority places for deeper modeling and analysis.
We hope that by providing a data-driven list of potential solutions, we can make it easier for planners to rank and sort the best opportunities for travel demand management. Instead of spending a ton of time generating a short list of project opportunities for consideration, we think planners can use our tool to identify the highest potential solutions for rigorous, deep-dive cost/benefit assessments. The goal is to drive a better return-on-investment in congestion mitigation solutions by giving planners the resources they need to comprehensively evaluate the options available. This theory was based on work we’ve done in several parts of the US, including a travel demand management project with our partners at SSTI, Michael Baker International, and the Virginia Department of Transportation.
To come up with the potential solutions, we made up our own rules about what solutions are indicated by specific travel patterns, which you can see here: https://www.streetlightdata.com/scoremethods. As you can see, we created a formula for each tactic. The percentages represent the approximate number of vehicle trips that could be converted to other modes by each tactic. In the future, we will give users the option to modify these pre-set assumptions. We know that local communities are going to have different criteria for this.
To sum up, our new Congestion Analysis lets you mix different types of contextual data sets and Big Data – location-based Services, navigation-GPS, and a blend of the two –into a single story. You can zoom in and zoom out to different types and times of day with ease. Finally, StreetLight InSight makes recommendations for different demand management solutions based on the results of these five different analyses. It helps you tell an interactive story of why congestion happens and how to solve it using real-world data.
However, even with the functionality that we’re introducing to the Congestion Analysis and to StreetLight InSight overall, at the end of the day this is just another tool for planners. A story doesn’t solve a problem. That’s what planners do. It’s simply designed to help you get the real-world information you need to solve our transportation challenges effectively and efficiently. The Congestion Analysis is meant to help you put the best Big Data resources to work – and it’s just the beginning of our new suite of storytelling enhancements for StreetLight InSight. As we continue building out these features, we want to hear your perspective.
What stories do you want to tell with Big Data? How can we help you tell them? Let us know in the comments below, send us an email, or set up a call. We want to you to inform our 2018 initiatives.