Category: Data

Slicing the crash data into interesting visualizations

The Chicago Crash Browser as it looks now. This only exists on my laptop and no place else. I can’t put it online because it’s so inefficient it would kill the server. 

I presented my Chicago Crash Browser to attendees of an OpenGov Hack Night three weeks ago and gathered a lot of feedback and some interest from designers and programmers there.

We collaboratively came up with a new direction: instead of focusing on creating a huge web application that I proposed, we (anyone who wants to help) would start small with a website and a couple of crash data visualizations. The visualizations would serve two purposes:

  • attract attention to the project
  • start building a gallery of data-oriented graphics that describes the breadth and extent of the crash data

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An enjoyable Friday morning collecting car speeds on Clark Street

Watch this 7 second video of a person driving a late model Toyota Camry in Lincoln Park at 50 MPH, next to the park. 

mean 30.83 mph
median 31
mode 30
min 17
max 50
frequency: 121 cars
greater than 30 mph: 65 cars
% greater than 30 mph: 53.72%

Statistics exclude the three buses counted at 26, 18, 20. Time was 8:23 to 8:38 on Friday, May 4, 2012, at Clark Street and Menomenee Street. The street width at where I collected the data is 65’9″ (789 inches). This location is eligible for a speed camera as it is within 1/8 mile of a park and is thus a “Children’s Safety Zone”.

I’m still working on the report for an article to be published on Grid Chicago. I used this Bushnell Velocity Speed Gun.

BikeLock app based on dataset I opened up

Bike parking at Daley Plaza, downtown Chicago. 

It’s really cool to see work you did “go places”. A friend of mine who works at Groupon just linked me to an iOS app called BikeLock that finds bike racks near you on iPhones, iPads, and iPod touches. It’s based on bike rack location data in the City of Chicago’s Data Portal. (The data on there is old, while the data in the public API I built is real time.)

Download it from the iTunes Store for 99 cents. The developer is Mike Jahn, another Groupon staffer. You can get the same information for free, though, on my mostly mobile-friendly Can I bring my bike on Metra? web app, and a website I made for the Chicago Department of Transportation (CDOT).

A screenshot of the Can I bring my bike on Metra? bike rack finder website. 

That data comes straight from the Bike Parking Web Application I started developing in 2008 soon after I started working in the Chicago Bicycle Program. It was good that my supervisor had the same perspectives I did about open and transparent data and work. But it didn’t start like that; here’s the full story:

My first job at the Bicycle Parking Program was to deal with abandoned bikes, get them off the street. I was taught the existing method of keeping track of my work, but I used my programming skills (in PHP, MySQL, and with the Google Maps API) to develop a web application that tracked it faster and mapped out the abandoned bikes I had to visit and tag with a notice. I was using this for a few days or few weeks and then show my boss. His reaction was something like, “Great! Now make one for bike racks!”

Why? Well, let’s take this quote from Judy Baar Topinka, Illinois comptroller, speaking Tuesday about her office’s new website, The Ledger, which lists the state’s unpaid bills among other financial data.

“The object of the exercise is to make everything that we know of in the comptroller’s office public. If we know it, you’ll know it.” WBEZ

I made one for bike racks. I created two environments, one for private administration at the office (“Bike Parking Web Application”) and one for the public (“public interface”). A later feature I added to the public interface was the Advanced Search. This allows you to filter by Ward, Community Area, and Status. You can then choose your sorting method. A map will appear above the results. You can download the results as either an XLS file, and XLS file that’s designed to be imported in GIS programs (like QGIS), or a KML file.

I’m aware of just one other app that uses this data set: MassUp.us. I don’t know if MassUp uses the real-time API that my Metra bike rack finder uses.

Figuring out how many CMAQ projects are for roads

Simplified, the purpose of Congestion Mitigation and Air Quality (CMAQ) grant is to fund projects that reduce congestion and improve air quality. This usually means bicycle, pedestrian, and transit facilities and vehicles. But it also means road projects. Like intersection widening, new signals, changes to signal programming, and “signal interconnect” (timing the signals to cooperate with each other to have some free flowing traffic). It can also mean making grade separations at railroad tracks to eliminate backups when trains cross. However, not everything is infrastructure: there’s also marketing, encouragement, analysis, bike sharing, and education.

In a conversation I was having last night with some transportation advocate friends, one joked that most of CMAQ funds road projects. I agreed (probably because the irony of reducing congestion by making higher capacity roads was funny to me), and we moved on to other topics. I set out verify the actual distribution share for the six-county region in Northeastern Illinois.

I spent almost an hour converting the Chicago Metropolitan Agency for Planning’s CMAQ 2012-2016 projects list from PDF to Excel and then quickly identified every project as being “road” or “not road”. I tallied the amount of proposed CMAQ funding for the projects to get the answer: road projects take up 25.7% of CMAQ funding.

But I can’t stop there! Now that I have CMAP’s data in a spreadsheet, I can get the average of Daily VOC eliminated for road and non-road projects, as well as the estimated cost per VOC kilogram eliminated.

On average, non-road projects have a lower cost per VOC kilogram eliminated ($4,109.37 versus $9,472.90). And non-road projects on average eliminate 19.7 times more kilograms of VOC daily (5.918 kg versus 0.301 kg for road projects).

There are some disclaimers! These are all estimates and not every project has received funding. Also, projects are not selected solely on cost per kilogram of VOC eliminated, or daily VOC eliminated. I’d also like to see estimates on the number of people affected by each project.

You can check my math by downloading my modified projects list (XLS).

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.