Tagbike crashes

Streetsblog Chicago reader David Altenburg left a salient comment this morning in response to the final tally of cyclists killed in Chicago last year after being hit by cars.

David’s comment about cyclist fatalities and red light cameras.

He wrote, “Is there any evidence that those cyclists who were killed were also issued improper tickets from red light cameras? Because if there is, then maybe we can get the current crop of ‘progressive’ mayoral candidates to give a shit about them.”

In 2013, three bicyclists died in car crashes, a fluke, because if you look at RedEye’s chart the annual average of bicyclist fatalities is 6 people. (There was a fourth cyclist death in 2013, but that was a train crash with the Brown Line.)

Crash statistics differences from 2011 to 2012

I posted this as a series of tweets on Friday night.

The following is an email conversation between myself and Travis Wittwer, a cool guy in Portland, Oregon, whom I stayed with in April 2010. We’ve had similar conversations before about the language writers (mainly newspaper article authors) use when speaking about and describing situations where “people and their bicycles make contact with people and their cars” (yes, there’s an easier way to say that, read on).

Cycling on Milwaukee Avenue at Grand Avenue and Halsted Street, one of the most crash-likely intersections on Milwaukee Avenue.

Someone asked me on Twitter: “What’s more dangerous, biking with no helmet or driving with no seatbelt?” It’s an odd comparison, but I decided to try to crack the question.

If your definition of “dangerous” is “the likelihood that you’ll receive an injury while traveling in/on the vehicle”, assuming that the likelihood of being in a crash is the same*, then you are more likely to sustain an injury while cycling while wearing a helmet than while driving or being a passenger in a car while wearing a seatbelt.

Here’s the data, for crashes in Chicago in 2007-2010:

Table 1: Yes, recorded to be wearing a helmet while bicycling

 Injury Type Frequency (each number is a person) Percent of total No injury 3 7.32% Possible injury 6 14.63 Non-incapacitating injury 26 63.41 Incapacitating injury 6 14.36 Fatality* 0 0 Total 41 100%

A value of 0 fatalities in four years for people wearing a helmet absolutely DOES NOT mean that a helmet prevented a fatality. The “contrary” data for “Recorded to not be wearing a helmet or having safety equipment” shows that there was 1 fatality in four years – the data do not suggest that the fatality would be prevented if the person was wearing a helmet. The sample size is so small that this data is meaningless.

Table 2: Yes, recorded to be wearing a seatbelt as driver or passenger

 Injury Type Frequency (each number is a person) Percent of total No injury 423,096 89.42% Possible injury 21,667 4.58 Non-incapacitating injury 23,956 5.06 Incapacitating injury 4,338 0.92 Fatality 93 0.02 Total 473,150 100%

*I don’t think we can determine the likelihood of being in a crash when riding a bicycle because we don’t know the “device miles traveled” of Chicago cyclists. It’s probably possible to approximate the number of vehicle miles traveled by drivers in Chicago, though; I’m not sure about passengers.

• Bicycling: All injuries
• Bicycling: No safety equipment or helmet wearing
• Bicycling: Unknown usage of safety equipment
• Auto: All injuries
• Auto: No safety equipment or helmet wearing
• Auto: Unknown usage of safety equipment

The United States Department of Transportation is holding a data visualization competition and Chicago bike crash locations are one of the topics.

From Michael Carney:

I started this project because, basically, I thought it would be interesting to make a map of bike crash locations around Chicago and present it to my GIS class at UIC. Sebastian Lew and I collaborated for several months and it evolved into something more. Using ArcGIS, we were able to symbolize streets by level of overall crash intensity, calculate crashes per mile on streets, perform hot spot analysis to identify areas with high numbers of crashes, compare ridership levels with crash levels, examine temporal trends in crash activity, and perhaps most importantly, assess the effectiveness (at least at a basic level) of current bicycle infrastructure. At the very least I hope our project can help you plan a safe route to work, at the most I hope it can be used by policymakers and planners when considering how and where to expand Chicago’s bike infrastructure.

I just finished creating a website that brings together my original Chicago bike crash map and all of its offshoots created by others. It also includes a more details and updated FAQ page as well as a short history of how the map and data came to be.

Right now it features projects from myself, Francesco Villa, Derek Eder, and George Aye’s students at the School of the Art Institute “Living in a Smart City” class.Â The site also links to my inspiration: Boston and San Francisco. If you have a related project, email me and I’ll figure out a way to add it to the site.

Last week you heard me on WGN 720 AM talk about bicycling in Chicago and my bike crash map.

This week you’ll get to see me talk about bike crash and dooring data on WTTW’s Chicago Tonight program. It comes after a rule change announced on Sunday: the Illinois Department of Transportation will begin collecting crash reports for doorings. Previously, these were “unreportable.”

WTTW reporter Ash-har Quraishi came over to my house Thursday to ask me about what kind of information the crash data I obtained from IDOT includes and excludes.

Whet Moser mentioned recently in the Chicago Magazine blog that he’s more afraid of spiteful comments from readers than new data that may show there’s a huge number of dooring bike crashes going on in Illinois.

Whenever an article about some modest improvement in the lives of bicyclists is published, in this case news that the state of Illinois is going to start tracking whenÂ bicycle accidents involve doorings, the comments section will inevitably be filled with vitriol, and I can’t help but read it. There’s no other public forum in which people wish death on their fellow citizens like the comments to a story about biking. And I find it grimly fascinating, like a moral gapers block.

In line with a story that aired Thursday night about doorings and this new rule about collecting data, WTTW channel 11 (Chicago’s PBS affiliate) started a discussion thread title, “Should drivers be more courteous and mindful of bikers?” I think WTTW has a wildly different audience than those who read the Chicago Tribune online. And the comments, so far, reflect this.

A fairly respectful (and unidentified) commenter suggested a great idea that may have a positive impact on visibility of bicyclists:

Perhaps bikers should be required to have a daytime running lamp on the front of their bikes so that they are more visible in a motorist’s side mirror?

I often ride my bike with my headlight on. This is not a half-bad idea!

Outfitting Chicago bicyclists with bike lights in Wicker Park.

On this Chicagoist story about how IDOT will now collect data on doorings (instead of ignoring that crash type as they preferred), I opened the story photo entitled “Cabbie takes down another” by Moe Martinez. His photo caption reads, “you see it alot … thankfully this guy seemed to be relatively ok … coherent and what not.”

I wanted to know just how often “we” see taxi drivers crashing with people riding bicycles. You can’t filter by vehicle type in either mine or Derek’s bike crash maps, but you can via the Fusion Table.

I decided to get the answer via Google Refine and make a screencast to show you just how quick and powerful a tool it is.

2. Click on the VEH1_SPECL column’s down arrow, then Facet>Text Facet.
3. In the facet box, sorted alphabetically, find “TAXI/FORE HIRE.”
4. The number of rows that apply is listed: 353.
5. Divide 353 by the total number of rows, 4931, multiply by 100, and you get your percentage.

Taxi drivers are involved in just 7.2% of bicycle crashes in Chicago in 2007-2009.

The majority of crashes, at 66%, involve people driving “PERSONAL” vehicles. And 80% of those crashes are with a passenger vehicle that’s not a van, minivan, SUV, truck, or bus (so probably a sedan or coupe). Let’s look at more data.

How many taxis are there and how many personal vehicles are there? Are taxicabs involved in a disproportionately higher number of crashes?

About 781,023 people drive to work, either alone or with someone else, in Chicago (data from 2005-2009 5-year American Community Survey). 1,063,047 households have 1,218,594+ vehicles available in Chicago. Let’s assume the 7,000 taxicabs in Chicago are not counted as a “vehicle available.”* That’s 1,225,594 “personal” vehicles. If all were on the road at the same time, only 0.57% of them would be taxicabs. But they’re not on the road at the same time. So let’s take that number of people who drive to work and add 7,000 vehicles to it. So of those 788,023 “vehicles” now on the road, just 0.88% of them are taxicabs.

So it does seem that taxicabs are involved in a disproportionate number of crashes when compared to their presence on the streets. However, taxicabs are most likely driven more more miles and for more time than personal vehicles thus making their exposure to people bicycling greater than drivers of other vehicles. (A majority of “personal” trips are very short.)

New data coming soon

I can’t wait to get the 2010 crash data. Here’s why: In 2007, students in a taxi driver training course at Harold Washington College received some education about sharing the road with bicyclists:

A pilot “Share The Road” education module was launched at the taxi training school at Harold Washington College. It includes a 25-30 minute lecture, with discussion. After the pilot, the class will be required for all people training to drive taxis in Chicago. In the future, bicycle questions will be included on the exams required to become taxi drivers. June 2007 MBAC meeting minutes (PDF).

The number of crashes between taxi drivers and people riding bikes jumped from 2007 to 2008, but declined heavily between 2008 and 2009. More data will show us a clearer trend that may lend insight into the impact of the “Share The Road” education module.

*Notes

The question (PDF) on the American Community Survey asks, “How many automobiles, vans, and trucks of one-ton capacity or less are kept at home for use by members of this household?” This may or may not include taxicabs stored at home.

I don’t know how many taxicabs there are in Chicago, but the Chicago Sun-Times reported there are approximately 7,000.

This screenshot from the Chicago Crash Browser map shows the location of bike-car collisions at Ogden/Milwaukee, an intersection that exemplifies the yellow trap problem the city hasn’t remedied.

List of the most crash-prone intersections on Milwaukee Avenue in Chicago. Using data from 2007-2009, when reported to the Chicago Police Department. Dooring data not included on the bike crash map. I used QGIS to draw a 50-feet buffer around the point where the intersection center lines meet.

Intersecting street (class 4*) Bike crashes
Chicago Avenue (see Ogden below) 12 (17)
California Avenue 9
Halsted Street & Grand Avenue 7
Damen Avenue & North Avenue 6
Western Avenue 6
Ogden Avenue (see Chicago above) 5 (17)
Ashland Avenue 5
Diversey Avenue 5
Fullerton Avenue 5
Elston Avenue 5
Augusta Boulevard (not class 4) 5

Combine the six-way (with center triangle) intersection of Ogden, Milwaukee, Chicago, and you see 17 crashes. Add the 6 just outside the 50-feet buffer and you get 23 crashes. Compare this to the six-way (without center triangle) at Halsted, Milwaukee, Grand, where there’s only 7 crashes.

What about the two intersections causes such a difference in crashes? Let’s look at some data:

 Ogden, Milwaukee, Chicago Halsted, Milwaukee, Grand Automobile traffic Approx 58,000 cars per day Approx 50,000 cars per day. Bicycle traffic Not counted, but probably fewer than 3,100 bikes More than 3,100 bikes per day* Bus traffic Two bus routes Three bus routes Intersection style Island; three signal cycles No island; one signal cycle

*Notes

Traffic counts are assumed estimates. Counts are taken on a single day, either Tuesday, Wednesday, or Thursday. Bike counts at Halsted/Milwaukee/Grand were actually taken on Milwaukee several hundred feet northwest of the intersection so DO NOT include people biking on Halsted or Grand! This means that more than 3,100 people are biking through the intersection each day.

Intersection style tells us which kind of six-way intersection it is. At island styles you’ll find a concrete traffic island separating the three streets. You’ll also find three signal cycles because there are actually three intersections instead of one, making it a 12-way intersection. Also at these intersections you’ll see confusing instructional signage like, “OBEY YOUR SIGNAL ONLY” and “ONCOMING TRAFFIC HAS LONGER GREEN.”

These intersections are more likely to have a “yellow trap” – Ogden/Milwaukee definitely has this problem. The yellow trap occurs at that intersections when northbound, left-turning motorists (from Milwaukee to Ogden) get a red light but they still need to vacate the intersection. Thinking that oncoming traffic has a red light but are just being jerks and blowing the red light (when in fact they still have a green for 5-10 more seconds) they turn and sometimes hit the southbound traffic. The City of Chicago acknowledged this problem, for bicyclists especially, in summer 2013 but as of November 2014 the issue remains.

Here’s a more lengthy description of one of the problems here as well as an extremely simple solution: install a left-turn arrow for northbound Milwaukee Avenue. The entire intersection is within Alderman Burnett’s Ward 27.

Source and method

I can’t yet tell you how I obtained this data or created the map. I’m still working out the specifics in my procedures log. It involved some manual work at the end because in the resulting table that counted the number of crashes per intersection, every intersection was repeated, but the street names were in opposite columns.

Crash data from the Illinois Department of Transportation. Street data from the City of Chicago. Intersection data created with fTools in QGIS. To save time in this initial analysis, I only considered Milwaukee Avenue intersections with streets in the City of Chicago centerline file with a labeled CLASS of 1, 2, or 3.