Transfer penalties

True story.

Today a complete stranger came to my house asking for directions to  the Huron Transit Station (I guess to get the 94 downtown to transfer to something, I am not clear what). More accurately, she asked my wife who was outside, who brought her in to the house, where I was.  My house is about 1 mile away from Huron station, so she was a bit lost.

The stranger was going to Richfield. Knowing Huron was a ways away, I went to the MetroTransit app to find directions to this address from where she actually was. The recommended was 3 transfers, but only a few minutes longer was a route that was 2 transfers, which I recommended (67C to Franklin Ave. LRT/Blue Line to Mall of America to the 5L) – which seemed far simpler. Stated time just under an hour. I am guessing the Transit app (website/mobile version) doesn’t penalize transfers the way a normal person (or a mode choice model) would.

I hope she made it.

The Missing Link: Bicycle Infrastructure Networks and Ridership in 74 US Cities.

Recently Published:

Seattle bike network
Seattle bike network

Abstract: Cities promote strong bicycle networks to support and encourage bicycle commuting. However, the application of network science to bicycle facilities is not very well studied. Previous work has found relationships between the amount of bicycle infrastructure in a city and aggregate bicycle ridership, and between microscopic network structure and individual tripmaking patterns. This study fills the missing link between these two bodies of literature by developing a standard methodology for measuring bicycle facility network quality at the macroscopic level and testing its association with bicycle commuting. Bicycle infrastructure maps were collected for 74 United States cities and systematically analyzed to evaluate their network structure. Linear regression models revealed that connectivity and directness are important factors in predicting bicycle commuting after controlling for demographic variables and the size of the city. These findings provide a framework for transportation planners and policymakers to evaluate their local bicycle facility networks and set regional priorities that support nonmotorized travel behavior, and for continued research on the structure and quality of bicycle infrastructure and behavior.
Keywords Bicycling · Travel Behavior · Networks