In this blog post, StreetLight Data’s Kim Harrison uses StreetLight InSight®, our easy-to-use web app that transforms Big Data into useful transportation analyses, to evaluate the causes of congestion on her morning commute from Walnut Creek, CA to San Francisco, CA.
My Morning Commute
I chose my home in Walnut Creek, a San Francisco suburb, because of its great school district, and because the shopping district and hospital are both a short walk from my house. However, I do have to drive myself to work and my children to school every morning, and there is typically so much traffic on the street in front of my house that I can't turn left out of my driveway. Instead, I have to turn right and follow a circuitous route with several right turns – this doubles the amount of time it takes to drop my kids off at school.
My home is on a frontage road along a major freeway, so when traffic on the freeway is bad, drivers take a freeway off-ramp to drive along the frontage road until they reach the next on-ramp. I decided to use StreetLight InSight to determine how many of the commuters blocking my driveway were my neighbors, and how many were freeway drivers. In other words, I asked what percentage of trips using the frontage road are local, and what percentage are external trips?
Analyzing Congestion with StreetLight InSight
At StreetLight Data, I regularly help my clients set up studies looking at this same type of cut-through behavior in other communities. They usually take just a few minutes – for example, this analysis was processed in less than four minutes. I set up my analysis using these parameters:
- Type of Trip: Personal trips (StreetLight InSight analyzes commercial and personal trips separately)
- Peak AM Day Part: 6am – 9am
- Average Weekday Type: Monday – Thursday
I set up analysis Zones in StreetLight InSight so that I could identify which trips were external and which trips were internal. I designated the following Origin Zones:
- Gates on the major freeways and arterials surrounding downtown Walnut Creek, which capture external trips
- Downtown Walnut Creek (my community), which captures internal trips
I chose my Frontage Road to be the Select Link, or “Middle Filter” in StreetLight InSight terms. My Destination Zone is the on-ramp to get back on the freeway at the end of the frontage road (see Figure 2 below). StreetLight InSight “locks” trips to roads, and our GPS data has 5 meter spatial precision, so we can get extremely precise about ramps and specific roads.
StreetLight InSight revealed that on an average day, for the entire day, 68.2% of trips that use my frontage road to access the freeway are internal trips that originate in Walnut Creek. 31.8% are external trips – or freeway drivers using my frontage road to “cut through.”
However, during my morning commute, only 40.2% of the trips are internal, and 59.8% are trips cutting through. With StreetLight InSight, it’s easy to visualize where these trips are coming from (see Figure 1 and Figure 2 below):
Figure 1: This StreetLight InSight heat map visualizes the relative volume of trips from each origin zone that use my frontage road to navigate to the freeway. The large orange Zone is downtown Walnut Creek. The surrounding green, yellow, and red “gate” Zones are the freeways and major arterials from which drivers navigate to my frontage road. My frontage road is the middle filter, marked by a purple dot. The destination zone (6) is the highway on-ramp on Route 680, which is shown as a grey rectangle with a black border above.
Figure 2: This StreetLight InSight chart shows the percentage of trips that originate in each Zone that use my frontage road to access the freeway. As you can see, more trips originate in Ygnacio Valley Road, outside of my downtown Walnut Creek community, than originate in my neighborhood.
Of course, this data just gives commuters like me just one piece of the puzzle. To really get my morning commute back on track, I need transportation engineers to design a solution! Do you have an idea? Share your solution in the comments!
INRIX, a StreetLight Data partner, provided the GPS data for this StreetLight InSight analysis. Click here to read more about our GPS data sources.