Tag: crash data

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.

Stats from the OECD: Comparing traffic injuries of the United States and Netherlands

May 21, 2012 / / 0 Comments

For an article I’m writing for Architect’s Newspaper about the Chicago Forward CDOT Action Agenda, I wanted to know about traffic injuries and fatalities in the United States, but compared to the Netherlands and Denmark and other places with a Vision Zero campaign (to have 0 traffic deaths each year).

I already knew the OECD had a good statistics database and web application. With a few clicks, I can quickly get a table of traffic injuries (casualties) listing just the countries I want. I can easily select the years I want, too.

In one more click the web application will show a time animated bar chart. A feature I’d like to see added is dividing the figure (in this case traffic injuries) by the population. Check out the video to see what it looks like. The United States looks to be in terrible shape, but our country has several times more residents.

I had trouble downloading and opening the CSV file of the data table I created. The XLS file was damaged, also. The built-in Mac OS X Archive Utility app couldn’t open the .gz file, but I used The Unarchiver app successfully.

My calculations, based on data from OECD (national population and traffic fatalities), Illinois Department of Transportation (IDOT), and the American Community Survey:

Fatalities per 100,000 in 2009

  • United States: 11.02472
  • Denmark: 5.48969
  • Netherlands: 4.35561
  • Sweden: 3.84988
  • Chicago: 16.74891
  • United Kingdom: 3.83555

Chicago’s fatality rate per 100,000 citizens in 2009 was 16.75 (473 deaths on the roads). The fatality rate dropped in 2010: just 11.65 deaths per 100,000 residents (315 deaths on the roads; the population also decreased).

Updated September 28, 2012, to add the United Kingdom. 

Terminology debate: crash versus collision

May 18, 2012 / / 0 Comments

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).

Travis: Continue reading

Slicing the crash data into interesting visualizations

May 17, 2012 / / 0 Comments

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

Continue reading

How high (and low) expectations can make traffic safer

February 20, 2012 / / 0 Comments

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.