Category: Data

Finding a new way to measure cities’ bike friendliness in the United States

November 3, 2012 / / 8 Comments

A really smart person could come up with a way to measure day-to-day bike friendliness based on how well cities adhere to standards that keep roads clear of obstructions that further frustrate the commute, like construction projects that squeeze bikes and cars together. 

I work at home. There are some days when I only leave my house to get milk from the Mexican grocery store at the end of my block (which makes awesome burritos). That means I ride my bike half as much as people who commute to work. on their bikes. Today I had a bunch of errands to run: drop off stuff, buy stuff, take pictures of stuff for my blog, Grid Chicago.

It was a very frustrating experience. I don’t need to go into details about how I was harassed by people who the state so graciously awarded a license to drive. But it happened. And it happens a hundred times a day to people cycle commuting in Chicago. I got to thinking about “bike friendly” cities. Is there a way to incorporate driver attitudes in there? I tweeted:

[tweet_embed id=264575958374305792]

Later I had the idea to use some very simple but objective measurements to create a new bike friendliness metric. It would help ensure that “Silver” (a ranking the League of American Bicyclists [LAB] uses) in one city means the same as “Silver”. It can expand from here but basically it works like this:

  • The share of people going to work who go by bike is a proxy for how “friendly” a city is to biking.
  • If a city has a lot of people biking to work, it must be friendly.
  • If a city has a few people biking to work, it must be non-friendly.
  • Cities are compared to each other to determine friendly and non-friendly.
  • The metric uses standard deviation to score cities.

Stop me if this has already been done.

I created a spreadsheet that lists the top 10 populous cities in the United States. I then added 10 more cities: Austin, Boston, Davis, Madison, Minneapolis, Portland, San Francisco, Seattle, and Washington, D.C. In the next column I listed their bike commute share from the American Community Survey 2006-2010 5-year estimates. I calculated the standard deviation and mean of these shares and then in another column used Apple Numbers’s STANDARDIZE function:

The STANDARDIZE function returns a normalized value from a distribution characterized by a given mean and standard deviation.

I think that’s what I want. And the output is close to what I expected. I then found the LAB ranking for each city and found the variance of each ranking to see how far apart each city within one ranking was from another city in the same ranking. The results were interesting: the higher the ranking, the more variance there was.

Hurricane Sandy prompted a lot of New Yorkers to bike. It made headlines, even. Photo by Doug Gordon. 

I wanted to add another metric of bike friendliness, and that’s density. To me, a higher density of people would mean a higher density of places to go (shop, eat, learn, enjoy) and friends and family would be closer, too. Or the possibility of meeting new people nearby would be higher. Yeah, I’m making a lot of assumptions here. So I applied the STANDARDIZE function there as well. I added this number to the previous STANDARDIZE result and that became the city’s score.

So, in this new, weird ranking system, the most bicycle friendly cities are…drum roll please…

  1. Davis, California (Platinum)
  2. New York City (Silver) *
  3. San Francisco (Gold) *
  4. Boulder (Platinum)
  5. Boston (Silver)
  6. Philadelphia (Silver)
  7. Tie: Chicago*, Washington, D.C. (Silver)
  8. Tie: Portland* (Platinum), Minneapolis* (Gold)

Remember, I said above that any author of a list should spend at least a day cycling in each city. I’ve starred the cities where I’ve done that – I’ve cycled in 5 cities for at least a day.

I only calculated 20 cities. Ideally I’d calculate it for the top 50 most populous cities AND for every city that’s been ranked by LAB.

LAB cities list (PDF). My spreadsheet (XLS).

Links between pedestrian safety and crime

October 25, 2012 / / 4 Comments

Chicago Pedestrian Plan

Safety item 20: Analyze the relationship between pedestrian safety and crime (download the plan)

The 2011 Chicago Pedestrian Crash Analysis identified a strong correlation between community areas with high numbers of pedestrian crashes and community areas with high crime rates. Correlation does not indicate causation and further study is necessary to understand this relationship and the potential broader benefits of pedestrian safety improvements. [From page 62 in the 2012 Chicago Pedestrian Plan.]

ACTIONS

Short Term

  • Identify and obtain funding for this study.
  • Identify a location for safety improvements and obtain data for the “before” conditions.

Mid Term

  • Design and implement pedestrian safety improvements.
  • Develop a pedestrian safety enforcement plan for the area for the duration of the project.
  • Analyze the effects on pedestrian safety and crime.

MILESTONES

  1. Initiate this study by 2013 and complete by 2015.

ADDITIONAL RESOURCES

National Highway Traffic Safety Administration. Data-Driven Approaches to Crime and Traffic Safety (DDACTS). 2011. [I don’t fully see the connection, but this reference was linked to a page on NYC Department of Transportation’s website.]

Pedestrian Crash Analysis

The summary report didn’t contain the word “crime”. The technical report contained 2 mentions, with an additional chart. They are quoted in the ordered list below. Download the summary report.

  1. In an examination of various factors including crime, income, race, language spoken, and Walk Score®, the strongest correlation found was between pedestrian crashes and crime
  2. Finally, crime statistics were compared to pedestrian crashes to determine if a correlation could be identified, using data from the Chicago Police Department (CPD) annual reports for 2005 through 2009. The annual reports include incidences of crime by Chicago Community Area (CCA). The statistics for the years 2005 through 2009 were averaged and compared to the aver- age number of fatal and serious injury pedestrian crashes over the same time period in each CCA. Of these factors, crime was the only variable that correlated to pedestrian crashes. Figure 1 shows the correlation between crime and pedestrian crashes was very high. However, there may be many variables responsible for this correlation.
  3. Figure 1: Crime vs. Fatal and Serious Injury Pedestrian Crashes by Chicago Community Area

Figure 1.

I have a few criticisms of this analysis: it lacks raw data; the data tables included in the technical report are of limited length, listing only the “top” items of any metric; the summary report lists many silly factoids; the maps are low resolution and of a limited scale – their design could be modified to improve their usefulness in communicating the crash frequencies of the marked locations. The analysis is reliable.

The technical report includes the state’s guide on how police officers are trained to fill out a crash report form. It also includes relevant crash reporting laws in Illinois. Download the technical report.

Special post for S.M.

Stolen Bike Registry data: Which train stations have the most bike theft?

September 28, 2012 / / 0 Comments

If you can help it, don’t park your bike on the sidewalk under the tracks at the Clybourn Metra Station. Too many opportunities for theft here. 

The Stolen Bike Registry is a website created by Chicagoans for people to notify the community that their bike has been stolen. I make no claims to the accuracy or completeness (or anything) about this list or the dataset from which it was created. Because of less than optimal data collection practices, and a diversity of website users, the location information is difficult to comb through and present. I’ve used Google Refine to clean up some of the location data so that I can pick out the theft locations that represent CTA or Metra stations.

This is a list of the most reported bike theft locations that are CTA or Metra stations, from about June 13, 2006, to April 2, 2011, representing 1,740 bike theft reports*. It’s not known how many bike thefts were reported to the police because they don’t know.

CTA (13 stations)

Logan Square Blue Line CTA 8
Rockwell Brown Line CTA 5
Addison Brown Line CTA 2
Fullerton Red/Brown Line CTA 2
Paulina Brown Line CTA 2
Western & Milwaukee (Blue Line) CTA 2
Western Brown Line CTA 2
Addison Blue Line CTA 1
Chicago Brown Line CTA 1
Damen Blue Line CTA 1
Ashland Orange Line CTA  1
Cumberland Blue Line CTA 1
Wellington Brown Line CTA 1

The new bike racks at Clybourn Metra station are in a more visible spot. Maybe there’s even a security camera pointed at them some of the time. 

Metra (24 stations)

Clybourn Metra 19
Ravenswood Metra 18
Edgebrook Metra 4
Evanston Main Street Metra 2
Forest Glen Metra 2
Healy Metra 2
Lake Cook Metra 2
Ogilvie Metra 2
57th Street Metra 1
College Avenue Metra Train Station 1
Corner of Maple & Church in downtown Evanston, near Metra 1
Glenview Metra Station 1
Harlem Metra Station Berwyn, IL 1
Irving Park Metra Stop 1
Jefferson Park Metra 1
LaSalle Street Metra 1
Mayfair Metra 1
Metra Station at Davis Street, Evanston 1
Morton Grove Metra Station 1
Prairie Crossing Metra Station 1
Rogers Park Metra 1
Union Station Metra 1
Western Metra Station 1
Wilmette Metra 1

* Reports come from around the world. 10 dates have been excluded because their dates were anomalous, empty, or not possible.

Updated September 30 to correct a Metra station and combine it with another.

My Chicago Card Plus tells me how often I use the CTA

July 9, 2012 / / 0 Comments

In this interview with Chicago Transit Authority president Forrest Claypool, I admitted to him and everyone else in the room (three bloggers and three CTA staff) that I rarely ride the CTA. The purpose of my admission was to explain how I gathered up so many questions. A lot of them come from friends and Grid Chicago readers. I always use my Chicago Card Plus to pay for fares because it’s extremely convenient: I never have to worry about having the correct fare and it can be replaced for a nominal $5 fee, protecting your money (the Chicago Card doesn’t have the same benefit because it can’t be registered). Anyway, it also tracks you and you can look up your history. I looked at it to understand just how rarely I use the CTA.

The Chicago Card Plus website shows your data in two ways: the last 5 transactions, and the last 90 days. It turns out that the last 5 transactions were beyond the 90 day period.

  • June 29, train (Blue Line)
  • May 22, bus (56/Milwaukee)
  • March 31, bus (I don’t remember which, but probably the Belmont bus with my mom)
  • March 31, bus

The fifth transaction was loading the card with more money. I think there was one other bus use on March 31, because the most recent two showed as transfer transactions. So I’ve added one more to the list.

  • March 31, bus

Five uses in 98 days, or 1 ride per 19.6 days.

Finding data about traffic and roads in Illinois

June 16, 2012 / / 0 Comments

There are two good websites that provide information about roads, traffic, and their many attributes. One is provided by the Illinois Department of Transportation (IDOT) called Getting Around Illinois (GAI). The second is the Traffic Count Database System (TCDS).

Both provide Average Daily Traffic (ADT) counts with TCDS making the information easier to find and presents more of it.

The GAI map has an important layer: jurisdiction. With that information you can determine who has “ownership” of a road. Jurisdiction has been an important factor in the nearly year-long delay of the Jackson Boulevard protected bike lane segment from Ogden Avenue to Halsted Street. IDOT has jurisdiction over this segment (which continues east to Lake Shore Drive; the road is also known as Route 66) and is requiring that the Chicago Department of Transportation do more analysis and revise their designs.

If you are looking for ADT counts, I highly recommend TCDS as it uses the more familiar Google Maps and doesn’t require the Microsoft Silverlight plugin (which is slow and often denigrated with poor usability applications).

GAI has truck routes and crash information as well.