CategoryResearch/Study

Playing around with Chicago data: who’s running red lights?

Range Rover with Illinois license plate "0"

A Range Rover with Illinois license plate “0” is seen moving 40 MPH in a 30 MPH zone through a red light at Ashland and Cortland.

I’m just seeing who’s driving around Chicago one night, using the Tribune-published dataset of over 4.1 million tickets issued from red light cameras.

The City of Chicago has installed at least 340 red light cameras since the mid-2000s to reduce the number of people running red lights and crashing. They’re supposed to be installed at intersections where there’s a higher-than-average rate of right angle (“T-bone”) crashes, which are more injurious than other typical intersection crash types.

Assessing safety wasn’t the Tribune’s story angle, though. It was about showing spikes in the number of tickets issued, which I verified to some extent. The article called the tickets issued during these spikes “undeserved” and “unfair”. The data doesn’t have enough information to say whether or not that is the case; a video or extensive photo review is necessary to rule out rolling right turns while the light was red (a much less dangerous maneuver unless people are trying to cross the street).

The first query I ran assessed the number of people who get more than one ticket from a red light camera. Since I was tired my query was a little sloppy and it missed a lot of more useful order choices and didn’t select the right fields. I fell asleep and started again in the morning. This time, I got it right in just two tries – I needed to try again because I mistakenly put HAVING before the GROUP BY clause.

Here’s the first query, in its final form, to retrieve the number of tickets for each license plate in each state (I assumed there may be identical license plates among states).

select max(ticket_number), max(timestamp), license_plate, state, count(*) AS count FROM rlc_tickets group by license_plate, state HAVING count(*) > 1 order by count DESC NULLS LAST

It resulted in 851,538 rows, with each row representing a unique license plate-state combination and the number of red light violations that combination received. You can reasonably assert that cars don’t change license plates more than a couple times in a single person’s ownership, meaning you can also assert that each row represents one automobile.

851,538 vehicles, which make up 35.1% of all violators, have received 2,601,608, or 62.3%, of the 4,174,770 tickets. (There are 2,424,700 license plate-state combinations, using the query below.)

select count(ticket_number) from rlc_tickets group by license_plate, state

Here’re the top 10 vehicles that have received the most violations:

  1. SCHLARS, IL, 78
  2. 9720428, IL, 59
  3. 8919589, IL, 57
  4. A633520, IL, 52
  5. 3252TX, IL, 45
  6. A209445, IL, 44
  7. N339079, IL, 44
  8. X870991, IL, 41
  9. 239099, IL, 41
  10. 4552985, IL, 40

The next step would be to design a chart to show these vehicles’ activity over the months – did the vehicles’ drivers’ behavior change, decreasing the number of red light violations they received? Did the vehicle owner, perhaps a parent, tell their child to stop running red lights? Or has the vehicle owner appealed erroneously-issued tickets?

When I ran one of the first, mistaken, queries, I got results that put license plate “0” at the top of the list, with only nine tickets (license plates with two or more zeros were listed next).

I googled “license plate 0” and found a 2009 Tribune article which interviewed the Range Rover-driving owner of license plate “0” and the problems he encountered because of it. The City of Chicago parking meter enforcement staff were testing new equipment and used “0” as a test license plate not knowing such that license plate exists. Tom Feddor received real tickets, though.

I then looked up on PhotoNotice the license plate and ticket violation number to find, indeed, the license plate belonged to someone driving a Range Rover at Ashland Avenue and Cortland Street on July 17, 2008. An added bonus was Feddor’s speed in that Range Rover: the camera recorded the car going 40 MPH in a 30 MPH zone.

I was done browsing around for the biggest offenders so next I wondered how many tickets were issued to vehicles licensed in Arizona, where U-Haul registers all of its nationwide vehicles. Arizona plates came in 29th place for the greatest number of tickets.

select count(*) AS count, state from rlc_tickets group by state order by count DESC NULLS LAST

As you may have expected, four surrounding Midwest states, and Ohio, rounded up the top five states after Illinois – but this isn’t notable because most visitors come from there and they each only comprise less than 1.3% of the total tickets. The next state was Florida.

  • 3,986,739, IL
  • 51,104, WI
  • 40,737, MI
  • 27,539, IN
  • 8,550, OH
  • 7,684, MN
  • 7,139, FL

What’s next: I’m working on finding a correlation between the number of reported crashes, and type, at intersections with red light cameras and the number of tickets they issued. I started doing that before running the numbers behind this blog post but it got complicated and it takes a long time to geospatially compare over 500,000 crash reports with over 4.1 million red light tickets.

What else do you want to know?

I will delete all comments that don’t discuss the content of this post, including comments that call red light cameras, or this program, a “money grab”.

Chicago wards with the most landmarked places

Montgomery Ward Complex

People float by the Montgomery Ward Complex on Kayaks. Photo by Michelle Anderson.

Last week I met with the passionate staff at Landmarks Illinois to talk about Licensed Chicago Contractors. I wanted to understand the legality for historic preservation and determine ways to highlight landmarked structures on the website and track any modifications or demolitions to them.

I incorporated two new geographies over the weekend: Chicago landmark districts, and properties and areas on the National Register of Historic Places (both available on the City of Chicago open data portal).

I used pgShapeLoader to import them to my DigitalOcean-hosted PostgreSQL database and modified some existing code to start looking at these two new datasets. Voila, you can now track what’s going on in the Montgomery Ward Company Complex – currently occupied by “600 W” (at 600 W Chicago Avenue) hosting Groupon among other businesses and restaurants.

Today I was messing around with some queries after I saw that the ward containing this place on the National Register – the 27th – also had a bunch of other listed spots.

I wrote a query to see which wards have the most places on the National Register. The table below lists the top three wards, with links to their page on Licensed Chicago Contractors. You’ll find that many have no building permits associated with them. This is because of two reasons: the listing’s small geography to look within for permits may not include the geography of issued permits (they’re a few feet off); we don’t have a copy of all permits yet.

[table id=15 /]

4 wards don’t have any listings on the National Register of Historic Places and nine wards have one listing.

Why are children getting hurt in the street because of “looming”?

Adults are better than children at detecting the speed of a car that’s traveling faster than 20 miles per hour and are more likely to avoid crossing, thus not getting hit. 

Director of New York City-based Transportation Alternatives Paul Steely-White asked on Twitter for a plain English translation of this three-year old journal article about vehicle speeds and something called “looming”.

The article is called “Reduced Sensitivity to Visual Looming Inflates the Risk Posed by Speeding Vehicles When Children Try to Cross the Road”.

Skip to the end if you want the plain English translation, but I’ve posted the abstract below followed by excerpts from Tom Vanderbilt’s Traffic.

ABSTRACT: Almost all locomotor animals respond to visual looming or to discrete changes in optical size. The need to detect and process looming remains critically important for humans in everyday life. Road traffic statistics confirm that children up to 15 years old are overrepresented in pedestrian casualties. We demonstrate that, for a given pedestrian crossing time, vehicles traveling faster loom less than slower vehicles, which creates a dangerous illusion in which faster vehicles may be perceived as not approaching. Our results from perceptual tests of looming thresholds show strong developmental trends in sensitivity, such that children may not be able to detect vehicles approaching at speeds in excess of 20 mph. This creates a risk of injudicious road crossing in urban settings when traffic speeds are higher than 20 mph. The risk is exacerbated because vehicles moving faster than this speed are more likely to result in pedestrian fatalities.

The full text is free to download, but I think Steely-White needs to learn more now, so I pulled out my favorite book about driving, Tom Vanderbilt’s “Traffic”.

Page 95-97:

For humans, however, distance, like speed, is something we often judge rather imperfectly. Unfortunately for us, driving is really all about distance and speed. Consider a common and hazards maneuver in driving: overtaking a car on a two-lane road another approaches in the oncoming lane. When objects like cars are within twenty or thirty feet, we’re good at estimating how far away they are, thanks to our binocular vision (and the brain’s ability to construct a single 3D image from the differing 2D views each eye provides). Beyond that distance, both eyes are seeing the same view in parallel, and so things get a bit hazy. The farther out we go, the worse it gets: For a car that is twenty feet away, we might be accurate to within a few feet, but when it is three hundred yards away [900 feet], we might be off by a hundred yards [300 feet]. Considering that it takes about 279 feet for a car traveling at 55 miles per hour to stop (assuming an ideal average reaction time of 1.5 seconds), you can appreciate the problem of overestimating how far away an approaching car is – especially when they’re approaching you at 55 miles per hour.

[Here comes the keyword used in the journal article, “looming”]

Since we cannot tell exactly how far away the approaching car might be we guess using spatial cues, like its position relative to a roadside building or the car in front of us. We can also use the size of the oncoming car itself as a guide. We know it is approaching because its size is expanding or looming on our retina.

But there are problems with this. The first is that viewing objects straight on, as with the approaching car, does not provide us with a lot of information.

[…]

If all this is not enough to worry about there’s also the problem of the oncoming cars speed. A car in the distance approaching 20 miles per hour makes passing easy, but what if it is doing 80 miles per hour? The problem is this: We cannot really tell the difference. Until, that is, the car gets much closer — by which time it might be too late to act on the information.

[the topic continues]

Plain English translation

However, nothing I found in Traffic relates children and “looming”. The bottom line is that children are worse than adults at detecting the speed of a car coming in the cross direction and thus decide wrongly on when to cross the street.

Update: Based on Vanderbilt’s writing, it seems that humans cannot really be taught how to compensate for looming, to build a better perceptual model in the brain to detect the difference between cars traveling 20 and 80 MPH. If this is true, and I’d like to see research of pedestrian marketing and education programs designed for children, it may be that we should stop trying this approach.

Revealing driver behavior on Clark Street with a radar gun

People prefer to cross Clark Street at Menomenee Street in groups of unacquainted individuals.

This is a more detailed post of the one at Streetsblog Chicago.

On the overcast morning of Friday, May 4, 2012, I recorded the speeds of 412 cars at four locations along Clark Street in Old Town and Lincoln Park for 15 minutes at each location. I missed counting the speeds of 42 cars. The embedded map shows the locations and some basic statistics.

What did I find? There’s a relationship between street width and the speed people drive. The highest speeds were found on the widest portions, and the lowest speeds on the narrowest portions. However, this basic study is far from scientific. A better study would record the locations simultaneously (necessitating 4 radar guns), calibrated equipment, consistent training for the researchers on data collection methods, a longer recording duration, and comparison to a control street that had a uniform width at four locations.


View Radar gun places on Clark Street in a larger map

1. Southbound Clark Street at Germania Place

My assistant and I set up the radar gun and camera immediately south of Sandburg Terrace and pointed the radar gun at people driving southbound on Clark Street between a row of parked cars at the concrete median (pedestrian refuge island). Classes would start soon at the Latin School on the east side of Clark Street. Compliance with state law requiring drivers to stop for pedestrians in the crosswalk was weak, to say the least, but compliance wasn’t explicitly measured.

  • Average speed: 17.21 miles per hour (MPH)
  • Maximum speed: 30 MPH
  • Cars measured: 151
  • Speed limit: 30 MPH
  • Drivers exceeding the speed limit: 0
  • Width: 224 inches (from west curb to pedestrian refuge island)
  • Effective width: 140 inches (excludes parking by subtracting 7 feet)
  • Crashes: 35, of which 4 were bicycle, and 3 were pedestrian.

Only one car-car crash (actually a 3 car crash) produced an injury. What’s interesting about this location is that in a lot of the crashes, the cars were traveling in the same direction. There’s a lot of school drop off and pick up activity here for Latin School of Chicago students, so it could be that many people are pulling away from the curb to merge into traffic and collide.

2. Northbound Clark Street at Menomenee Street

  • Average speed: 30.83 miles per hour (MPH)
  • Maximum speed: 50 MPH
  • Cars measured: 121
  • Speed limit: 30 MPH
  • Drivers exceeding the speed limit: 53.72%
  • Width: 395 inches (from east curb to dividing line). This includes the parking lane but no cars were parked within 50 feet, north and south, of the measurement location.
  • Crashes: 20, of which 2 were bicycle, and 1 were pedestrian. Many of the non-bike and non-ped crashes involved a parked car or taxi. The only injuries experienced were by the 2 cyclists and 1 pedestrian.

3. Northbound Clark Street at Lincoln Park West

We stood on the “pie” (traffic island) that separates northbound Clark Street traffic from northbound Lincoln Park West traffic to measure the traffic driving on Clark Street between the pie and the concrete median separating it from southbound Clark Street.

  • Average speed: 25.60 miles per hour (MPH)
  • Maximum speed: 40 MPH
  • Cars measured: 58
  • Speed limit: 30 MPH
  • Drivers exceeding the speed limit: 27.59%
  • Width: 252 inches (from concrete median curb to west curb on the pie)
  • Crashes: 4, of which 1 was bicycle, and 2 were pedestrian.

4. Northbound Clark Street between Lincoln Park West and Dickens Avenue

This location is 125 feet north of the previous location.

  • Average speed: 22.54 miles per hour (MPH)
  • Maximum speed: 35 MPH
  • Cars measured: 58
  • Speed limit: 30 MPH
  • Drivers exceeding the speed limit: 2.44%
  • Width: 264 inches (from east curb to dividing line).
  • Effective width: 180 inches (excludes parking by subtracting 7 feet)
  • Crashes: 0

Me measuring speeding drivers on Clark Street with the speed gun, my clipboard and paper, and a GoPro camera to record the speeding drivers and the results on the speed gun. 

Bike Walk Lincoln Park’s proposal

In 2011, Michelle Stenzel and Michael of Bike Walk Lincoln Park published a document to “Make Clark a Liveable Street“. The first two pages show an aerial photo of the same section of Clark Street where I measured automobile speeds, North Avenue and Armitage Avenue. On the first page, existing conditions are laid out. The second graphic shows proposed improvements.

At Menomonee Street, measurement location 2, the document says “pedestrians must cross 6 lanes with no safe haven”, a width of just under 66 feet. In the later pages, the first existing condition is blatant: “Wide lanes of auto traffic moving at speeds in excess of the speed limit”. My analysis in May demonstrates this.

How does BikeWalk Lincoln Park propose to “transform this stretch from a car-oriented ‘super-highway’ to a people-oriented liveable street”? By installing protected bike lanes, putting the street on a diet, and installing new and well-marked crosswalks among other ideas.

Width and speed summary

Ordered by location:

  1. 224/140 inches. 0% of drivers exceeded 30 MPH speed limit
  2. 395/395 inches. 53.72% of drivers exceeded 30 MPH speed limit
  3. 252/252 inches. 27.59% of drivers exceeded 30 MPH speed limit
  4. 264/180 inches. 2.44% of drivers exceeded 30 MPH speed limit

Ordered from narrowest to widest to see how width relates to speed:

  • 224/140 inches. 0% of drivers exceeded 30 MPH speed limit
  • 264/180 inches. 2.44% of drivers exceeded 30 MPH speed limit
  • 252/252 inches. 27.59% of drivers exceeded 30 MPH speed limit
  • 395/395 inches. 53.72% of drivers exceeded 30 MPH speed limit

Notes

Crash data is within 100 feet to avoid the overlap of the final two locations, which were 125 feet apart. Crash data comes from the Illinois Department of Transportation for 2005-2010. The Bushnell Velocity Speed Gun was borrowed for this analysis. The radar gun was filmed to show a speeding car and its speed simultaneously. The video below shows a driver traveling at 50 MPH in a Children’s Safety Zone (as it’s within 1/8 mile of a park, Lincoln Park, making it eligible for automated speed enforcement).

Curiously, no traffic counts have been collected on Clark Street near any of the count locations.

View the video on Vimeo.

Screenshot of traffic count website. Go to the Traffic Count Database System and search for “1700 N Clark Street, Chicago, IL” in the map. 

Where does this road diet rule come from?

55th Street road diet from summer 2012. This is the best road diet photo I’ve got. Traffic counts here indicate 15,700 cars daily (based on a single day of measurement in 2006).

“Roadways with Average Daily Traffic (ADT) of 20,000 or less may be good candidates for a road diet and should be evaluated for feasibility”, via FHWA. The documents – here’s the second one – I’ve found so far on FHWA’s website don’t explain the research behind this assumption. How should a road be evaluated for feasibility? The second one bases review of a street on crash type, severity, and rate.

View 4600 W Foster Avenue in a larger map. Alderman Laurino is correct in her description of how many lanes are here. The road is only striped for 1 lane in each direction.

This concerns me because CDOT seems to have adopted this as a policy. They are using it as a reason to not consider a road diet on Foster Avenue. However, though, Foster Avenue between Pulaski Road and the Edens Expressway has only “1 and a half lanes” in each direction, according to local Alderman Marge Laurino of the 39th Ward (see John Greenfield’s interview below, which is an expanded version of one published on Grid Chicago in two parts).

Interview

Greenfield: Where in your ward would you like to see speed cameras installed?

Laurino: Well right now I don’t know that we have locations that would fit some of the criteria that we’re looking at. Currently I think the ones that they’re putting in are going to be where there have been pedestrian fatalities and I don’t know that I have anything that fits that really strict criteria but I would… Just a suggestion, Foster Avenue in front of Gompers Park. I mean it’s often times an area where cars really speed because for whatever reason, where there are no homes and that and it’s just wide-open parkland people just seem to hit the accelerator. I don’t know why that it but it appears to be the case.

JG: Is that a long stretch with no stoplights?

ML: From Pulaski to Cicero it’s a long stretch and it’s not one lane. I want to call it one-and-a-half lanes. There really shouldn’t be two lanes of traffic going in one direction but they seem to squeeze that in. So anyway that might be a potential place for a camera. We’re also looking at something called a road diet, where we just, through paint markings and paint striping, make the street narrower. That would be on Foster Avenue, let’s say between central Park and Cicero.

JG: Is there any talk of putting in bike lanes there to take up the extra space?

ML: No, for whatever reason it doesn’t fit their criteria.

Survivor bias: Who walks away from automobile crashes?

This photo of a damaged car has little to do with this post. 

Then my friend Alex E. asked, “Is there a reason why?”

I can’t leave such a question hanging. I thought I read that somewhere, and it was probably in Tom Vanderbilt’s book, Traffic. What I found in there mostly referred to trucks (the semi-trailer type) because of their mass and how people not driving trucks behave around them on the road. The second part explained the statistics around who lives and dies in crashes involving a drunk driver.

Knowing that, and knowing the story I tweeted a link to, you’ll see that the event didn’t involve a truck and my relating them was perhaps unsuitable. It did involve drunk driving, but I may have misread the book text.

Here’s what Traffic says about trucks

“When trucks and cars collide, nearly nine of ten times it’s the truck driver who walks away alive.” Vanderbilt discusses how that is (page 247).

…we all likely have proof of the dangerous nature of trucks. We have seen cars crumpled on the roadside. We’ve heard news stories of truck drivers, wired on stimulants, forced to drive the deregulated trucking industry’s increasingly long shifts. We can easily recall being tailgated or cut off by some crazy trucker.

Just one thing complicates this image of trucks as the biggest hazard on the road today: In most cases, when cars and trucks collide, the car bears the greater share of what are called “contributory factors”.

Really? Car drivers caused crashes with trucks and then die from it?

Instead of relying on drivers’ accounts, he [Daniel Blower at Michigan Transport Research Institute] looked at “unmistakable” physical evidence. “In certain crash types like head-ons, the vehicle that crosses the center much more likely contributed to the crash than the vehicle that didn’t cross the center line”.

After examining more than five thousand fatal truck-car crashes, Blower found that in 70 percent of cases, the driver of the car had the sole contributing responsibility in the crash.

Basically, the car drivers in a car-truck crash caused the crash and ended up being the ones dying.

…the reason trucks are dangerous seems to have more to do with the action sof car drivers combined with the physcial characteristics of trucks and less to do with the actions of truck drivers. “The caricature that we have that the highways are thronged with fatigued, drug-addled truck drivers is, I think, just wrong”, Blower said.

“In a light vehicle, you are correct to be afraid of them, but its not because the drivers are disproportionately aggressive or bad drivers”, Blower said. “It’s because of physics, truck design, the different performance characteristics. You can make a mistake around a Geo Metro and live to tell about it. You make that same mistake around a truck and you could easily be dead.”

What Traffic says about drunk driving

Of the 11,000 drunk-driving fatalities studied by economists Steven D. Levitt and Jack Porter, 72% were the crash-causing drunk driver or their passengers, and 28% were the other drivers (most of whom were not drunk themselves) (page 251).

I need a visualization tip for showing pedestrian and auto traffic in downtown Chicago

Madison Street over the Chicago River. Pedestrian traffic is very high, and very constrained, near the Metra stations.

Here’s the goal:

Show that pedestrians don’t get sufficient space or time to have a high quality pedestrian experience given that they comprise the largest mode share on streets in the Loop. The trips are highly delayed at traffic signals, pedestrian space is encroached upon because of automobile turning movements, and the sidewalks aren’t wide enough for two-way or even one-way traffic at certain times of the day. It’s possible to build our way out of pedestrian traffic…

Here’s an example data set:

On October 3, 2006, for all of the 24 hours, at 410 W Madison Street, there were 17,100 automobiles counted.

On some day in summer 2007, for 10 hours, at 350 W Madison Street, there were 43,987 pedestrians counted.

The two locations are practically the same as the bridge here prevents more pedestrians or automobiles from “slipping in”.

It’s possible to download the data sets from CDOT’s Traffic Tracker so you can see the whole city on your own map, but you’ll have to do some digging in the source code to find them.

Tell it, Sue Baker! Car crashes are not accidents

“It was an accident!”, said the driver. Photo by Katherine Hodges. 

Because of Hurricane Sandy, the New York Times paywall is down so I’m reading every article I can, starting with “Safety Lessons from the Morgue“:

As she explains it, “To say that a car crash is an accident is to say it’s a matter of chance, a surprise, but car crashes happen all the time, and the injuries that people sustain in those crashes are usually predictable and preventable.”

Another car crash-related excerpt from the article about Sue Baker, injury prevention researcher extraordinaire:

In one of her recent projects, Baker looked at another aspect of highway deaths. The study, which Baker prepared with David Swedler, a doctoral candidate, examined more than 14,000 fatal crashes involving teenage drivers. They found that male drivers were almost twice as likely as female drivers to have had high levels of alcohol in their blood and were also more likely to have been speeding and driving recklessly. Significantly, 38 percent of 15-year-old drivers, both male and female, were found to have been speeding, but by age 19, female speeders dropped to 22 percent, while male speeders remained steady at 38 percent.

Those differences, Baker says, suggest that boys and girls should not automatically receive the same driver training — and that boys should perhaps receive their license at an older age than girls. “Males might scream foul,” Baker acknowledges, “but let them.”

Yes, let them. It’s too easy to get a driver’s license in this country.  I love her style:

In 1979, at a Department of Transportation public hearing about the dangers faced by truck drivers, Baker angrily explained, “Isn’t it time we did some crash testing with trucks and dummies, rather than with drivers themselves?” Later, according to Baker, the trucking industry hired a researcher to try to discredit her driver-safety studies. Unable to uncover problems with her work, he eventually gave up and called to tell her about his assignment. [emphasis added]

Not everything is perfect with injury prevention studies, though.

In the mid-1970s, [Sam] Peltzman did research on highway fatalities that suggested that mandatory safety features like seat belts and padded dashboards actually encouraged people to drive less cautiously.

Tom Vanderbilt talked about that in “Traffic“, which is basically my favorite transportation book, even mentioning Mr. Peltzman. Flip to page 181 to read it. Vanderbilt lists all of the different labels for that behavior:

  • the Peltzman effect
  • risk homeostasis
  • risk compensation
  • offset hypothesis

He summarizes: “What they are saying, to crudely lump all of them together, is that we change our behavior in response to perceived risk, without even being aware that we are doing so”. But Sue has a response:

Baker acknowledges that there may be some individuals in cars with anti-lock brakes, for example, who may not apply the brakes as soon as they did with the old brakes. But she insists there is no evidence that better brakes or air bags have encouraged recklessness — that they have in fact saved many thousands of lives. “What concerns me,” she says, “is that these spurious arguments are used by companies to bolster their opposition to beneficial safety regulation.

I think it’s safe to say now that she’s a personal hero of mine. But way, there’s just one more thing!

As she talked about what still needed to be done, her voice was tinged with anger: “Buildings need to be designed so it’s not so easy to fall down stairs. All new homes should have sprinklers. Traffic lights should be timed for pedestrians, not to move as many cars as possible through an intersection.

Yep. Exactly what we don’t do. We make ’em wait. And wait. Without even telling people the traffic signal’s even acknowledged their presence.

More

Links between pedestrian safety and crime

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.

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.

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