Tag Archives: crosswalk

Comments on a safety-in-numbers study

The University of California has published a study of pedestrian crashes in Oakland, California,

The Continuing Debate about Safety in Numbers—Data from Oakland, CA
Judy Geyer, Noah Raford and David Ragland, Traffic Safety Center;
Trinh Pham, Department of Statistics, UC Berkeley
UCB-ITS-TSC-2006-3

The full report is available online:

http://www.escholarship.org/uc/item/5498×882

John Forester, founder of the Effective Cycling program of cyclist education, and statistician, has demonstrated that the Safety in Numbers claim of Jacobsen (also cited in the Oakland paper) is faulty. Due to faulty math, a random set of numbers will generate the curve that apparently shows a decreasing crash rate with increasing numbers of users. This is not to say that the safety-in-numbers claim is false, but rather that Jacobsen has provided no evidence to support it. (Forester also questions Jacobsen’s explanation for safety in numbers as applied to bicyclists, but that’s a different issue.)

The Oakland report expresses the same complaint about Jacobsen’s math, and goes on to use better math to look for answers. Here’s a quote from page 5 (PDF numbering) of the Oakland report:

However, others are concerned that correlating collision rate (C/P) with pedestrian volume (P), (where C equals collisions and P equals pedestrian volume) will almost always yield a decreasing relationship due to the intrinsic relationship of the variable P and the fraction 1/P.

Tom Revay has generated a Microsoft Excel Workbook demonstrating how Jacobsen’s curve may be generated with  random data. Press the F9 key on a PC to refresh the random data. (Press Command [Apple] and = at the same time on a Mac. I thank Dan Carrigan for this information)

The Oakland study came up with some interesting and intriguing results. Here are a few; please correct me if I am wrong:

Pedestrians vs. Collisions/Pedestrian

Figure 4, p. 17, Pedestrians vs. Collisions/Pedestrian

  • The graph on p. 17, PDF numbering (click to see a larger version) shows the characteristic downward curve due to faulty math. However, the curve slopes back upwards for the intersections with the very highest numbers of pedestrians.
    p. 16, Pedestrians vs. Collisions

    Figure 3, p. 16, Pedestrians vs. Collisions

    A better graph (graph on p. 16, PDF numbering, click to see a larger version) shows crashes increasing with a steeper slope for the higher-volume intersections, worst at the intersections with the highest volume. Crash numbers are low enough, though, that the results for individual intersections are not statistically significant.

  • The Oakland study examines different intersections in the same community over the same time period rather than the same intersections at different times, or different communities with different volumes of pedestrian and vehicular traffic. The study can establish whether the safety in numbers effect applies only under the conditions it examined. Data from different times of day might possibly be checked against traffic volumes, though the results would be less robust and effects of lighting, alcohol use etc. would make them harder to interpret.
  • It is clear that a few intersections are outliers, with many more crashes than others. These intersections would be high on a priority list for improvements — though the actual numbers for individual intersections, again, are too low to be statistically significant.  The problem with lack of statistical significance highlights the importance of applying research data and operational analysis in determining where to make infrastructure improvements — crash data for an individual intersection are not statistically robust unless the intersection has an extremely bad problem. You apply research results and operational analysis so you can avoid collecting data on each intersection by killing and injuring people.
  • (See Results, p. 9, PDF numbering) Number of lanes on the primary and secondary streets, and number of marked and unmarked crosswalks, did not correlate with crash rates! (But note that this result is consistent with data on bicycling showing that riding on arterials is safer than on residential streets).
  • Despite the safety-in-numbers finding, the intersections with the largest numbers of crashes are still those with high pedestrian volumes. Increasing numbers decrease the rate of crashes, but not the number of crashes.
  • p. 18, Vehicles vs.Collisions/Pedestrian

    Figure 5, p. 18, Vehicles vs.Collisions/Pedestrian

    The crash rate increases for pedestrians as the number of vehicles increases (page 18, PDF numbering), though less rapidly than the number of vehicles. Is there a safety in numbers effect for vehicle operators as the number of vehicles increases? Yes, the likelihood that any particular driver will collide with a pedestrian decreases with the amount of vehicular traffic passing through an intersection — though the study doesn’t report this. The study doesn’t answer whether the result is achieved by improved signalization at high-volume intersections, or by depressing pedestrian volume (risk homeostasis), or by what other effect. The study also doesn’t say anything about crashes overall, as it doesn’t report on crashes not involving pedestrians.

All in all — interesting, intriguing, and careful research — but more research is needed!

Livable Streets proposal lacks credibility

I’m looking at a GOOD magazine/Streetsblog proposal for a “livable street”

This is a prime example of what I call the Photoshop school of traffic engineering. Anyone with computer graphics skills can generate a before-and-after comparison like this. Often, it looks very attractive to the untrained eye — but, whether the proposed changes make sense is another issue entirely.

It would be nice if the Streetsblog people who created this graphic had a few more clues about street design. Some of the issues:

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Guest posting: John Ciccarelli on the NYC Broadway bikeway

[John Ciccarelli is a consultant on bicycling, League of American Bicyclists Cycling Instructor and member of the Bicycle Technical Committee of the National Committee on Uniform Traffic Control Devices. These comments are based on his observations during a field trip to examine bicycle facilities in New York City in December of 2008.]

Broadway bikeway, Manhattan

Broadway bikeway: clogged with pedestrians

For me, the pedestrian conflicts on a new unconventional Manhattan bikeway — on the pedestrian-enhanced blocks of Broadway starting south from Times Square — rendered that bikeway nearly useless — even though those blocks of Broadway are similar to the
9th Avenue layout in several ways:

  • Both streets are multi-lane one-way-southbound
  • Both have a left-curbside one-way bikeway
  • At intersections there is a bike signal and a left-turn pocket and turn-arrow for motor vehicles (where the cross street is two-way or one-way-left) Continue reading

Comparing crosswalk and bike box

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