Here are several comments to the Echo in the City blog and to Streetsblog, on the subject of bike counters and research methods. Bicycle infrastructure should support bicyclists who are bicycling now. More infrastructure can of course inspire people to bicycle, but we ought to respect people who are using the bicycle to travel already. Changing the population of bicyclists through provision of infrastructure and police crackdowns on helmets or riders is not necessarily a positive act.
The advantage of the bicycle is that it offers mobility to people without requiring a large investment. People who have already figured this out should not be marginalized and penalized for not meeting bicycling standards set by authorities without democratic consent.
Thinking through the Strava data My response:
Can you point me to the part of your argument where you disproved the null hypothesis? The null hypothesis being that for planning purposes, the Strava-user database does not differ from other tools used to assemble data on cyclist behavior?
I agree strongly with the sentiments expressed in the “research-0013.jpg” cartoon, but I can envision a number of different methods that share the same problems. In New York City, the authorities do “screenline” counts, where counters are positioned along certain high-traffic bike routes leading to midtown Manhattan. This is great for finding out how many people are traveling to midtown, but in my opinion it is unlikely to lead to improvements to bicycle infrastructure along routes that do not lead to midtown Manhattan. My point being, the city authorities didn’t need to buy a Strava data pack to get data that would have similar biases. If the goal of cycling promotion is to get people onto bikes, the overall problem with all types of collection of cyclist data trips is that they only measure trips taken by people who are actually cycling during the study period.
My understanding of bicycling promotion market research is that transportation planners devote a great deal of attention to encouraging the “interested but concerned” folks who are not currently riding bikes because they feel it’s not safe. These people’s biking experiences are not going to be reflected in any kind of data collection project because they are not currently biking.
Do We Need Automated Bike Counts My response:
Great post. I like your Venn diagram. Looks to me though that the biggest problem with automated counters is that the level of detail of the information they provide is not likely to be required to prove the hypotheses that are being proposed.
If I tell you that 1531 people are bicycling through the intersection of West 86th St & Columbus Avenue in a southerly direction on an average summer Tuesday, what are you going to do with that information? Would you do something else if I told you the count was 3531? I presume any number greater than 0 could be used to justify some kind of bicycle infrastructure.
And in Streetsblog
Collecting data only on the number of people crossing between from borough to borough, but not counting “local” bicyclists, privileges people who are traveling longer distances, and the bike infrastructure necessary to encourage them, viz. better bridge crossings, greenways, and protected bike lanes along direct, arterial roadways.
Bicycles, however, are used for more than just traveling between areas. It is a canard that many car trips are just a mile or so and can be replaced by bicycle trips without having to confront issues of fatigue or fitness, thus reducing motor vehicle traffic in busy neighborhoods. This is the philosophy behind DOT-supported bike share, and the DOT neighborhood slow zone program, and it is therefore a little surprising that DOT researchers are still using screenline methods to collect data that does not inform the policy initiatives of the organization.