Category: Data

How high (and low) expectations can make traffic safer

I have low expectations of fellow Chicagoans who are moving their vehicles on the same roads I cycle on. I expect that every door will fling open in my path, causing me to be doored. I also expect to be cut off at any moment, and especially in certain places like at intersections (where the majority of crashes occur), bus stops, or in places with lots of parallel parking activity. Because of these expectations I feel that my journeys have been pretty safe. My low expectations cause me to ride slower, ride out of the door zone, and pay attention to everyone’s maneuvers.

This is another post inspired by Traffic: Why we drive the way we do (and what it says about us) by Tom Vanderbilt. From page 227 of “Traffic”, about expectations :

Max Hall, a physics teacher in Massachusetts who often rides his collection of classic Vespas and Lambrettas in Rome, says that he finds it safer to ride in Rome than in Boston. Not only are American drivers unfamiliar with scooters, he maintains, but they resent being passed by them: “In Rome car and truck divers ‘know’ they are expect not to make sudden moves in traffic for fear of surprising, and hurting, two-wheeler drivers. And two-wheeler drivers drive, by and large, expecting not to be cut off.”

The scooter drivers have high expectations, and it seems that they’re being met.

This all plays nicely with the “safety in numbers” theory about cycling: the more people who are riding bicycles, the more visible bicycling is, and the more aware a driver will be around people who are bicycling, and the more they will expect someone on a bicycle. Awareness means caution.

It’s difficult to gauge the safety of cycling in Chicago as we’ve no exposure rate: we don’t know how many people are cycling how many miles (nor where).

A cyclist waits for the light to change at Milwaukee Avenue and Ashland Avenue. 

Exposure rate

Exposure rate in the sense I’m using it here means the number of times someone is in a crash or injury for each mile they ride. We know how many crashes and injuries are reported each year (in the Illinois Motorist Crash reports), but we don’t know how many miles people ride (neither individually nor an estimated average).

There was a limited household survey of Cook County residents in 2008 from CMAP, called Travel Tracker, that collected trip distance information for all trips members of a household made on all trip modes – I haven’t looked into this yet.

It would be highly useful if the Chicago Department of Transportation conducted ridership counts at the 10 intersections with the highest crash rates. And if the 10 intersections changed the following year, the new intersections would just be added to the initial 10 to track the changes of the initial 10. This would be one step closer to being able to determine a “crash rate” for each intersection.

Crashes by bike or by foot at different intersections

While working on a private web application that I call Chicago Crash Browser, I added some code to show the share of pedestrian and pedalcyclist crashes. The site offers users (sorry I don’t have a web server that can make it public) a list of the “Top 10” intersections in terms of bike crash frequency (that’s bike+auto crash). You can click on the intersection and a list will populate showing all the pedestrian and pedalcyclist crashes there, sorted by date. At the bottom of the list is a simple sentence that tells what percentage pedestrian and pedalcyclists made up at that intersection.

I’m still developing ideas on how this information may be useful, and what it’s saying about the intersection or the people using it.

Let me tell you about a few:

Milwaukee Avenue and Ogden Avenue

I mentioned in my article Initial intersection crash analysis for Milwaukee Avenue that this intersection is the most bike crash-frequent.

23 crashes within 150 feet of the center, 2005-2010

82.61% bike crashes **

17.39% ped crashes.

Ashland Avenue and Division Street

28 crashes within 150 feet of the center, 2005-2010

46.43% bike crashes

53.57% ped crashes **

Milwaukee, North and Damen Avenues

46 crashes within 150 feet of the center, 2005-2010

39.13% bike crashes

60.87% ped crashes **

Halsted Street, Lincoln and Fullerton Avenues

38 crashes within 150 feet of the center, 2005-2010

42.11% bike crashes

57.89% ped crashes **

Montrose Avenue and Marine Drive (Lake Shore Drive ramps)

11 crashes within 150 feet of the center, 2005-2010

90.91% bike crashes **

9.09% ped crashes

Why do you think some intersections have more of one kind of crash than the other?

People walking at Milwaukee-North-Damen.

The Chicago Crash Browser can be made public if I have a host that offers the PostgreSQL database. Do you have one to offer?

Some crash analysis based on gender/sex in Chicago

A friend sent me an article saying that in London, women were experiencing crashes more often than men while cycling (BBC article). He asked if this was true about Chicago. So I crunched the numbers. This is very low-level, initial, take it with a grain of salt analysis. It appears that that is not the case for Chicago.

It appears that men walking or cycling are involved in disproportionately more crashes with automobiles than women, but not very disproportional.

1. Men make up 72.73% of people cycling (to work, the only trip purpose for which I have data). And they experienced 75.75% of the crashes with automobiles (to where is unknown).

2. Men make up 48.45% of people walking (to work, again, the only trip purpose for which I have data). And they experienced 53.38% of the crashes with automobiles (again, to where is unknown).

This analysis also points out shortcomings in our data. Even with National Household Travel Survey I don’t think I could get very detailed (as the statistics would be too aggregated and the sample size for Chicago would be small). This data is based on two sources: motorist crash reports from 2007-2010 from the Illinois Department of Transportation (IDOT); and American Community Survey “means of transportation to work”. The last time a household travel survey was done in Chicago was 2008 and I just acquired that data last week. I need to figure out how to connect the people and trip tables and then I can do more analysis, getting exposure data for all trips, not just work.

Who bikes?

Who bikes? pie chart

From April 2011, via Sightlines Daily, using data from John Pucher and Ralph Buehler, who got it from the 2009 National Household Travel Survey.

Contrary to popular convention, the biggest share of bicyclists isn’t yuppies, it’s low income people. In fact, the lowest-earning quarter of Americans make nearly one-third of all bike trips. Among that group, I would expect to find at least some fraction of working poor, students, the unemployed, and retired people of modest means. No doubt there are almost as many reasons to bike as there are cyclists, but it’s clear that bikes are a favored choice among those on a budget.

The big takeaway for me, however, is looking beyond low-income riders. Bicycling is remarkably evenly distributed among the remaining three quartiles. With the exception of the over- represented bottom quartile, bike trips don’t appear to be the province of any one income class more than any other.

Dumke fighting the open data fight for Chicagoans

Dan O’Neil mails a FOIA request to Chicago’s 311 service in 2007. Now, you can email most places (or fax!). 

I like to say that for every dataset a government agency proactively publishes, there’s one fewer FOIA* request it has to respond to.

City officials say they get so many FOIA requests that responding to them all has become a serious resource drain. But this is one of the reasons why—we don’t have any other way to get information about our government.

As a result, I will be adding to their workload and submitting another FOIA request. I don’t mind saying this publicly since it won’t be a secret anyway. That’s because the Emanuel administration has resumed Daley’s old habit of posting FOIA requests online. It’s also kept up Daley’s habit of not posting any information showing how responsive the city is.

That’s Chicago Reader author Mick Dumke talking about his troubles obtaining some data from the Chicago Department of Human Resources. Read the entire article, where he also gives a pretty good description of the “Chicago FOIA way”, the process for getting information in Mayor Emanuel’s transparent administration.

Note: I submit a FOIA request to some agency at least once a month. My most frequent FOIA requests go to the Chicago Transit Authority (CTA) and the Chicago Department of Transportation (CDOT). I also query the Chicago Police Department, and the Department of Administrative Hearings. Derek Eder has a story on how he and his colleagues worked with some Chicago staff to add new data about lobbying to the Chicago Data Portal.

*Freedom of Information Act. In California, it’s called FOIL, or Freedom of Information Law.