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Android versus iOS: my Chicago Bike Laws experience

November 21, 2013 / / 14 Comments
Chicago Bike Laws: dooring info

Screenshot of Chicago Bike Laws, highlighting the dooring law.

For all this talk that more people use Android, and Android has the biggest and still-growing chunk of the smartphone market (in the United States and the world), I’m not seeing that reflected in how many downloads there are of my two apps.

Chicago Bike Laws is a free app that has been available for Android (download) since November 4 and on iOS (download) since November 9, a 5-day difference. Yet the iOS version has had more installations (58) since then while people have downloaded the Android version 32 times (but 5 people removed it).

What gives? The app is exactly the same for both platforms.

Are Chicago bicyclists more likely to have iPhones? I don’t do any platform-specific promotion so you can count that out.

(The experience I’ve had with Chicago Bike Guide activity is different because the Android version came online over a year later and has always been a paid app – Android apps cannot switch between free and paid while iOS apps can. By the way, the Chicago Bike Guide is free for iOS right now and half-off for Android. The comparison is that the adoption rate is much slower for the Android version.)

Why do speeding crashes in Chicago lead to worse injuries?

November 21, 2013 / / 6 Comments

Don’t git behind me. Photo by Richard Masoner. 

A discussion about Chicagoans’ proclivity for tailgating (on a post about speed cameras) prompted me to look at the prevalence of this in causing crashes. I looked at the three-year period of 2010-2012 first, mainly so the numbers wouldn’t be so large, and left this information in a comment. But considering the prerequisites* for a crash to be reported in this dataset, and my desire to compare two multi-year periods, I switched my analysis to the single four-year period 2009-2012.

2009-2012

Total crashes: 318,193. Total fatalities: 554 people.

Tailgating crashes

62,080 crashes, 19.53% of all crash types

Tailgating crashes, injuries breakdown:

  • Killed: .0012 (this represents the number of deaths per crash). 75 people died in these crashes, representing 13.54% of all deaths.
  • Incapacitating injuries: 8.53% (the average distribution of people’s injuries in all tailgating crashes)
  • Non-Incapacitating: 46.32%
  • Possible injury: 45.15%

The share of all crash types that are tailgating has increased steadily from 18.11% in 2009 to 20.79% in 2012.

Speeding crashes

10,339 crashes, 3.24% of all crash types

Speeding injuries:

  • Killed: .0118 (this represents the number of deaths per crash). 122 people died in these crashes, representing 22.02% of all deaths.
  • Incapacitating injuries: 15.55% (the average distribution of people’s injuries in all speeding crashes)
  • Non-Incapacitating: 51.95%
  • Possible injury: 32.50%

The share of all crash types that are tailgating has decreased slightly from 3.72% in 2009 to 3.02% in 2012. While speeding leads to fewer crashes, it leads to a greater incidence of death and serious injury. The probability of a speeding crash leading to at least one death seems to stay steady through the period while the probability of seeing a person with an incapacitating injury versus a different kind of injury varies more, but not so much in a range that overlaps the rates for tailgating crashes.

A future comparison at injuries should look at the top crash causes for death and serious injury.

N/A and Unable to determine crashes

237,729 crashes, 74.71% of all crash types

N/A and unable to determine injuries:

  • Killed: .0013 (this represents the number of deaths per crash). 305 people died in these crashes, representing 55.05% of all deaths.
  • Incapacitating injuries: 9.38% (the average distribution of people’s injuries in all N/A crashes)
  • Non-Incapacitating: 48.26%
  • Possible injury: 42.35%

Notes

Updated December 4, 2013

I updated the wording on how to interpret these numbers. For example, previously for “killed” there was a percentage saying this number represented the amount of crashes that had at least one death. This wasn’t accurate: the same number represents a rate of deaths per crash of that type. Injury percentages represent the distribution of injury types experienced by all the people injured in crashes of that type.

Reliability

Analyzing crash causes is not very reliable as 45.60% of the reported crashes in 2012 had “N/A” or “unable to determine” listed as the primary cause! The third and fourth most frequently ascribed causes were the two tailgating codes (described below). There are some crashes that had the one of these two causes in the secondary cause field but I haven’t calculated that.

Cause code descriptions

Each crash has two cause codes. For tailgating crashes I searched for reports where “failing to reduce speed to avoid crash” or “following too closely” in either the primary or secondary cause field (it’s possible that a report had both of these causes ascribed). For speeding crashes I searched for “speed excessive for conditions” or “exceeding speed limit” in either the primary or secondary cause fields.

Prerequisites

This data excludes crashes where there was no injury or no property damage greater than $500 (2005 to 2008) and $1,500 (2009 to 2012). You cannot compare the two datasets when you want to see a share of all crashes because the number of “all crashes” will be underreported in the second dataset.

Queries

These are some of the MySQL queries I used to get the data out of my own crash database (I’m figuring out ways to make it public, using a shared login). “Cause 1 code” indicates the primary cause of the crash according to the police officer’s judgement. “Cause 2 code” indicates the secondary cause of the crash according to the police officer’s judgement.

1. Crash cause reliability: SELECt count(casenumber), sum(`Total killed`), `Cause2`, `Cause 2 code` FROM `CrashExtract_Chicago` WHERE year = 12 GROUP BY `Cause 2 code`  ORDER BY cast(`Cause 2 code` as signed)

2. Speeding crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 1 OR `Cause 1 code` = 27 OR `Cause 2 code` = 1 or `Cause 2 code` = 27) AND year > 8

3. Tailgating crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 3 OR `Cause 1 code` = 28 OR `Cause 2 code` = 3 or `Cause 2 code` = 28) AND year > 8

4. N/A and Unable to determine crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 18 OR `Cause 1 code` = 99) AND year > 8

You can have your free parking when I get my free cappuccino

November 20, 2013 / / 22 Comments

Kudos to this Chicago developer and their architect for blending the parking garage into the building. I still dislike that it’s visibly a parking garage. 

My friend Payton Chung has some very dry urban planner humor. Which I absolutely love. He wrote about parking minimums in Washington, D.C., and the current proposed zoning change that would reduce them (and included a reference to Chicago’s parking “podiums”). The best part is below:

Drivers’ inability to find free parking spaces outside their offices is no more deserving of a public policy response than my inability to find a free cappuccino waiting outside my office.

Free parking makes the world go round, doesn’t it.

That wasn’t a joyride on Lake Shore Drive

November 14, 2013 / / 2 Comments

Video starts at Ohio Street (you can see the W Hotel after the curve at Ontario Street); the camera holder and driver speak with expletives.

Craig Newman at the Sun Times is wrong about the person in this video, who was filmed riding a Divvy bike-share bike along the jersey barrier on northbound Lake Shore Drive. He blogged today:

All excellent questions. But let’s maybe simplify and throw a warning sticker on the bikes: NO RIDING ON EXPRESSWAYS

And yes, I am a consistent bike commuter who enjoys the benefits and routinely laments stupidity, four-wheeled, two-wheeled and on foot we all have to fight through daily. But come on. Lake Shore Drive?

This person didn’t want to be cycling there. There are several ways one could make the mistake of riding a bike on this roadway. And once you’re on, you’re on for good until the next exit (which in this Divvy rider’s case is 1/4 mile north from where the video was shot).

She might have known there was something called the Lake Shore Path (as some people call it) or the Lakefront Trail – she couldn’t remember which. She didn’t see any “Route X” signs, or “Interstate Y” signs.

She saw a road that looks like so many others. It’s called a drive, not an expressway (it doesn’t meet those technical standards). She most likely entered from Lower Wacker (which connects to Michigan Avenue, where many people ride Divvy against Alderman Reilly’s desire) and went up the center, northbound ramp to Lake Shore Drive.

Stony Island Avenue in Chicago. The only difference between this and Lake Shore Drive is the more frequent stopping (unless there’s congestion on LSD) and the shopping. Photo by Jeff Zoline.

It can be easily mistaken for a typical road, looking similar to the stroads near wherever she lives. Like Stony Island, Cicero, Columbus, Archer, in Chicago, or any countless “major street” in the suburbs. Maybe she comes from Roscoe Village, where Western Avenue goes over Belmont, or Bridgeport/Brighton Park, where Ashland Avenue goes over Pershing Avenue. Or some other city where regular roads cross other regular roads at different grades.


View Larger Map

Local photographer Brent Knepper tweeted that he made the mistake before.

We have a problem with our design such that the highway didn’t sufficient communicate, “No really, you shouldn’t bike here”. On the contrary, we have roads that should be shouting, “Hey, you really should be biking here!”

Maybe that’s why Netherlands makes it perfectly clear with red pavement.

Believe me, not even Casey Neistat would ride up here intentionally.

Updated with a better guess of where she entered Lake Shore Drive.