On 5/30/2019 4:07 PM, John B. Slocomb wrote:

snip

"While the policy implications of this work point to protected and
separated bike infrastructure as part of the solution, we need to keep
in mind that these approaches are complementary and should not be
considered in isolation. Moreover, our results - particularly the
safety disparities associated with gentrification - suggest equity
issues and the need for future research."

It's also important to understand that a city doesn't need to cover
every single foot (or mile) with protected bike lanes in order to make a
difference. Selecting the areas where problems most often occur is often
sufficient, and choosing one route out of many possible routes for a
protected bike lane is adequate, you don't have to have every parallel
road with identical infrastructure. This is what cities around here do,
we look at where protected bike lanes will have the most effect and
concentrate our financial resources on those areas.

Also, be very careful when looking at the statistics of how ridership
levels change. Sometimes an area will have a steady increase over a long
period of time then all of a sudden have one bad year. An anomaly can be
a weather event, a natural disaster, or a host of other things. Some
people intentionally take numbers completely out of context in an effort
to mislead people. I can tell you that bicycle commuting in Silicon
Valley probably fell significantly for 2019 because we've had an
extremely wet winter and spring. Last year we had an unprecedented
number of bad air days due to large wildfires which led to less cycling.

For example lets look at Pittsburgh, PA. From 1990 to 2017 they had a
240.4% increase in those 27 years. From 2006 to 2017 they had a 67.4%
increase over 11 years. From 2011 to 2017 they had a 2% increase over
six years. But there was a drop of 45.2% from 2016 to 2017. You can't
ignore a long-term huge increase and then look only at a single year─
that kind of cherry=picking of statistics is extremely dishonest and is
something that you often see when someone is trying to manipulate
statistics to suit a particular agenda.