Many of our clients are concerned with new modes of travel and how they interact with existing transportation. Composed of services like Uber, Lyft, Postmates, and Instacart, “Gig Driving” for riders and delivery has been a persistent concern. And its impact on congestion is hotly debated topic at conferences, in the press and among friends. Some claim it makes congestion better (less parking or less personal car driving), and others claim it makes congestion worse. The biggest challenge to finding the answer is a deep lack of available data about this mode of transportation.
Our own data team at StreetLight suspects the answer is “it depends.” We hypothesize that the interaction between Gig Driving and Congestion depends heavily on what we call “context,” i.e. location, existing transit, urban density, land use, time of day, etc. We also believe that Gig Driving is here to stay and that we can arm policy makers with data to avoid the desire to “undo” what is a mobility megatrend — and instead try to harness and accelerate positive effects on the community and transportation networks, while mitigating the negative ones.
To test our hypothesis about granular variation, we used our access to billions of transportation data points, and a lot of expertise in data science and transportation. We measured the interaction between Gig Driving and congestion road-by-road throughout the Greater Miami region.