Tag Archives: research

Another deceptive poster

More evidence that the anti-car crowd can’t think its way out of a paper bag. Even when they could make a much better case for themselves.

Claim of space occupied by motor vehicles.

Claim of space occupied by motor vehicles.

The text, in Italian, reads “space necessary to transport 48 persons: auto, electric car, robotic car.”

Only, the cars aren’t transporting anyone. They are all parked. They would take up much more space if in motion, just to have a safe following distance. The robotic cars would take up somewhat less space, due to their quicker reaction time for braking, but still much more than shown in the picture.

Twice before on this blog, I’ve shown similar posters making similar claims, and each time, they have shown parked vehicles.

Here, Muenster, Germany poster.

Here, Seattle, Washington, USA poster.

M. Kary on the epidemiological approach to traffic-safety research

M. Kary has released the manuscript of his paper on the unsuitability of the epidemiological approach in studying traffic safety.

Unsuitability of the Epidemiological Approach to Bicycle Transportation Injuries and Traffic Engineering Problems
Author: M Kary
Injury Prevention 2015;21:73-76, Published Online First 14 August 2014

First paragraph of the abstract:

Bicyclists and transportation professionals would do better to decline advice drawn from characteristically epidemiological studies. The faults of epidemiology are both accidental (unpreparedness for the task) and essential (unsuitability of the methods). Characteristically epidemiological methods are known to be error-prone, and when applied to bicycle transportation suffer from diversion bias, inappropriately broad-brush categorisations, a focus on undifferentiated risk rather than on danger, a bias towards unsafe behaviour, and an overly narrow perspective. To the extent that there is a role for characteristically epidemiological methods, it should be the same as anywhere
else: as a preliminary or adjunct to the scientific method, for which there is no

You may read the entire manuscript here:


Monsere, Dill et al. — Not Yet a Review, But…

M. Kary, who prepared a review of the Lusk et al Montreal study, has had a preliminary look at the Monsere, Dill et al. study of barrier-separated on-street bikeways (“cycle tracks”) which the bicycle industry lobby PeopleforBikes is promoting as demonstrating their safety. Dr. Kary has given me permission to publish his comments here.

An Introduction To and Overview Of:
Monsere C, Dill J, et al. (2014) Lessons From The Green Lanes: Evaluating Protected Bike Lanes In The U.S. Final Report, NITC-RR-583

To begin with a platitude: traffic accidents are rare events. The totals are large only because the overall volumes of exposure are huge. Therefore, if considering safety in terms of outcomes rather than the underlying mechanisms of operation, any facility, no matter how poorly designed, will appear safe if examined over a short period of time.

But collecting data over a long period of time has its disadvantages too: not just cost and delay, but also the averaging, and therefore blurring, of the effects of various changing causes and circumstances. Nor does it work at all for facilities that are yet to be built. In response to these problems, engineers developed the methods of traffic conflict analysis. They can be seen as based on the following logical and kinematic necessities. First, in order for a collision to occur, the vehicles involved must eventually get on a collision course. Second, in order to get on a collision course, they must first get on a near-collision course. On the other hand, not all vehicles once on collision or near-collision course do end up colliding: their operators make course corrections and avoid that outcome. Such potentially dangerous but often ultimately safe trajectories, i.e. traffic conflicts, occur much more frequently than actual collisions, deaths, or injuries. If there exists a suitable relationship between the former and the latter, then conflict analysis can be used to study road safety at reduced cost, with better timing, and even via simulation modelling of facilities that have been designed but not yet built.

The theory and practice of conflict analysis for motor vehicles has been developed over something like a half a century of research. This has evolved to quantitative methods using not just traffic cameras, but also instrumented vehicles, automated data extraction, and theoretical concepts such as time to collision, gap time, gap acceptance, post-encroachment time, and many others. There is no such corresponding body of research for bicycles. Even if there were, it could never be as important to bicycle or pedestrian deaths and injuries as it is for the occupants of cars and trucks: for example, the latter vehicles never topple over at stops or just slip and fall, so that their occupants fracture an arm or strike their heads on a curb. In fact the majority of bicyclist injuries, even those requiring hospitalization, apparently involve only the bicyclist, making conflict analysis entirely or at least largely irrelevant to them.

On the other hand collisions with motor vehicles are major factors in cyclist deaths and injuries, and they are what cyclists worry most about. And even apparently bicycle-only crashes can be provoked by e.g. general fears or specific intimidations, or avoidance manoeuvres leading to loss of control. Thus there are also dimensions of traffic conflicts applicable to bicycling, but either inapplicable or less so to motor vehicle-only conflicts. Nor is every conflict visible or strictly kinematic: consider for example the effects of sudden and loud horn honking or engine revving.

With these fundamental limitations in mind, obviously traffic conflict analysis is a promising method for investigating important aspects of bicycling safety. The theory needs to be developed, so we can figure out what constitutes a high or low rate of conflicts, what types of conflicts figure what way into which accident types, and how vehicle operators and pedestrians cope with them, such as through hypervigilance, or avoidance of the area and thus diversion of problems to a different one.

Not only does the theory need to be developed, but also the methods of data extraction and analysis: the subjective review of traffic camera recordings, typically of low quality, is a mind-numbingly tedious, labour-intensive and error-prone task, that does not scale well.

The work of Monsere et al. (2014), Lessons From The Green Lanes: Evaluating Protected Bike Lanes In The U.S., should be considered a pilot project in this effort, although the authors themselves do not describe it as such.

Monsere et al. aimed to address six questions:

  1. Do the facilities attract more cyclists?
  2. How well do the design features of the facilities work? In particular, do both the users of the protected bicycle facility and adjacent travel lanes understand the design intents of the facility, especially unique or experimental treatments at intersections?
  3. Do the protected lanes improve users’ perceptions of safety?
  4. What are the perceptions of nearby residents?
  5. How attractive are the protected lanes to different groups of people?
  6. Is the installation of the lanes associated with measureable increases in economic activity?

Apart from noting that, as with most sociological research, their survey response rates were dismally low (23-33% overall, counting even only partially completed surveys as full responses), to produce a socioeconomically skewed sample (e.g. the bicyclists being 89% white, 68% male, 82% having at least a four-year college degree, and 48% with annual incomes over $100,000)— this overview of their work considers only the first part of their question No. 2.

Monsere et al. installed video cameras along short bicycle sidepaths (“protected lanes”, “cycle tracks”) constructed between approximately the summer of 2012 and the early summer of 2013 as part of the Green Lanes Project. These were in four U.S. cities, San Francisco (two 0.3 mile paths), Portland (one 0.8 mile path), Chicago (0.8 and 1.2 mile paths) and Washington (a 1.12 mile path; no cameras were installed in Austin, although sociological surveys were conducted there). They did their video recording chiefly at intersections, six in these four cities in the summer and fall of 2013. This was then presumably while the users were still in a cautious or exploratory state, as they got used to the new facilities.

Only 12-18, or in one case 20, independent hours of video were analyzed from each intersection. As each intersection examined was given a unique treatment, results cannot easily be pooled. These are very small numbers.

(This makes for substantially less than 120 hours total. The authors seem to say they analyzed 144 hours of video at intersections. This would mean that some of this total came from multiple cameras examining the same intersection at the same time. The authors do show frame captures from some of their cameras. This observer would find it difficult to correctly identify the conflicts from the views on display.)

As noted following the opening platitude, any facility, no matter how poorly designed, will appear safe if examined over a short enough period of time.

The six facilities examined were all so new (less than or little more than a calendar year old) that there were no injury or death data available for them. (For comparison, the entire city and island of Montreal, with all its thousands of intersections, averages of late about five cyclist deaths and 25-50 police-recorded serious cycling injuries per year.) Thus, there would not have been a way to use even many more hours of recording to examine for any relationship between the surrogate outcomes (conflicts, violations or errant behaviours) and the outcomes of most interest, deaths and injuries.

Further, as this was neither a before-after study nor a comparison with standard intersections, there is no way to know whether the numbers of observed conflicts, violations, or errant behaviours, were themselves high or low.

As to the actual results from this pilot project, the much touted headline was that there were only six minor conflicts found, out of nearly 12,900 bicycle movements through intersections. The most basic problems with this headline are:

1. It is the wrong comparison. The conflict rate has to be the number of conflicts divided by the number of occasions where at least two users capable of conflicting are present, e.g. a bicycle and at least one other bicycle, pedestrian, or motor vehicle. Thus the authors give figures of 7574 turning motor vehicles, but only 1997 turning motor vehicles with bicycles present. The corresponding conflict rates (which they normalize by the products of bicycle and motor vehicle movements, not by the numbers of bicycle movements alone) they give for the individual intersections therefore vary by factors of approximately 3 to 10, depending on which figures are used.

2. Six is the total of observed “minor” conflicts, not the total number of observed conflicts. There were also 379 “precautionary” conflicts with motor vehicles, 216 with pedestrians, and 70 with other bicycles.

3. Besides conflicts, there were numerous violations or other errant behaviours: e.g. 9-70% of bicycles and 7-52% of turning motor vehicles in the various intersection designs used the lanes incorrectly, 1-18% of turning motor vehicles in the various mixing zone designs turned from the wrong lane, 5-10% of motorists turned illegally on red arrows at intersections with bicycle-specific signals, and 7-23% of bicyclists disobeyed their signals.

4. Without any theory or model of how any of these occurrences or their frequencies relate to death, injury, or property damage, and without any before-after or non-sidepath comparison data— not to mention, with the very small numbers of observation hours— there are almost no safety implications, positive or negative. The only concrete result is that one of the local authorities apparently deemed the problem of motor vehicles turning from the wrong lane (18%), straddling lanes (another 17%), or entering the turn lane early (15%) to be so severe that they later removed the intersection treatment and replaced it with another design (at Fell and Baker in San Francisco).

5. The sociological surveys tell another story: one-third of all bicyclists surveyed said they had been involved in at least one near collision on the paths, while 2% experienced an actual collision. 23% had a near collision with turning cars, 1.8% an actual collision with turning cars; 19% a near collision with a pedestrian, and 0.4% an actual collision with a pedestrian.

In short: this is an interesting pilot project, whose methods are impractical for the amount of data collection needed for meaningful safety results. Even with better methods, conflicts are only one facet of the bicycling, and overall safety picture; while road designers and road users, whether bicyclists or motorists, have to consider more than just safety. Convenience, transit time, cost, and greenhouse gas emissions also matter. A cycle track that, like the downtown de Maisonneuve track in Montreal, lies largely dormant in the winter, but delays motor vehicle traffic in the winter and ties it up spring, summer and fall, will be of no help in reducing CO2 emissions. The much touted headline results from this study are selective, overblown, and misleading. Any facility will appear safe if examined over a short enough period of time, and surely 12 to 20 hours each is short enough.

Barrier features

The same barrier can have more than one of the characteristics listed below, and they may be different for different types of vehicles.

  • Containment: The barrier prevents a vehicle from, for example, going over a cliff, or straying into oncoming traffic. Examples: curbs, guardrails, Jersey barriers.
  • Deflection: The barrier guides a vehicle that has gone off course back into the intended direction of travel. Examples: Jersey barriers, guardrails.
  • Threat: The barrier is hazardous in itself, so drivers shy away from it. Example: boulders, rigid bollards.
  • Sham: The barrier appears to pose a threat of damage to a vehicle but in fact is designed to minimize or avoid damage. Example: flex posts.
  • Stop: The barrier is intended to stop a vehicle approaching it.
  • Energy-absorbing: The barrier is designed to lengthen the time and so decrease the severity of an impact — same idea as with air bags or helmets. Examples. crash cushions, deformable barrier walls.
  • Warning: The barrier generates an audible or visual warning. Examples: rumble strips, proximity alarms.
  • Virtual: The barrier is established using signs, signals or markings and the laws which pertain to them.

A barrier may be benign for dual-track motor vehicles, yet  overturn single-track vehicles. These can topple over a low guardrail or Jersey barrier. A sham barrier for dual-track vehicles such as a flex post can tangle with the pedal or leg of a bicyclist, becoming a threat barrier. Reflectorized pavement markers, which are little more than a virtual barrier for dual-track vehicles, can throw a bicyclist –see this video example.

These considerations are lost in the design of many bicycle facilities. Barriers that are hazardous to bicyclists are being used because they are normal traffic-engineering practice, sometimes only due to lack of knowledge but sometimes enforced through design standards.

On the other hand, a high railing with a handlebar rub strip can serve as an effective and safe deflection barrier for bicyclists, even though it may be too weak to contain a heavier dual-track vehicle.

In Orlando, Florida recently, I saw two other examples of misuse of barriers:

  • Flex posts used ahead of and behind a parallel parking space which had been reconfigured as a bicycle parking station. Motorists parking in the next spaces would expect a light, stopping impact if they moved too far forward or back at very low speed. The colloquial expression is “kissing bumpers.”  Lacking this warning, a motorist already had backed up into the flex posts and damaged one of the bike racks. Here, rigid bollards or a guardrail would be appropriate.
  • Raised reflectorized pavement markers are being used on bike lane lines, neglecting the fact that bicyclists must enter and leave the bike lane, and often do best to ride along its edge. Nationally recognized guidelines specifically prohibit the use of raised markers here, for that reason.

The most common misused barrier for bicyclists is probably the low railing, which will topple a bicycle over. That is seen in many different varieties, ranging from the conventional Jersey barrier or guardrail to low wooden curbs lining boardwalks, to hand-height railings alongside paths.

Review of the Austin shared-lane marking report

The City of Austin, Texas, working with researchers from the University of Texas, has prepared a report on shared-lane markings. This is available at


I understand that this report also has been published in the Journal of the Institute of Traffic Engineers.

The Austin team has also prepared reports on colored bike lanes, bike boxes and the Bicyclists May Use Full Lane sign.

My critique of the shared-lane marking report follows.


Executive Summary

First, safe bicyclist behavior was defined by three factors: (1) riding in the lane position indicated by the sharrow, (2) not riding outside of the lane (on the sidewalk or in empty parking spaces), and (3) not riding alongside queues of stopped vehicles.

None of these indices defines safety in any consistent way. Riding in the indicated lane position may or may not be safe, depending on conditions. Riding in empty parking spaces may be safe if a long string of them is empty. Riding alongside queues of stopped vehicles may also be safe, depending on lateral clearance, speed etc.

Second, safe motorist behavior was defined by three factors: (1) motorists give adequate space to bicyclists when passing, (2) motorists did not encroach on adjacent lanes when passing, and (3) motorists make complete lane changes when passing.

The first of these criteria defines safety. I can’t make any sense of the second. Just as in their Bicyclists May Use Full Lane report, the authors describe merging partway into an adjacent lane as “encroaching” — but with a shared-lane marking in one lane, it is hard to imagine how a motorist would overtake without using the adjacent one. Criterion 2 and criterion 3 seem to contradict one another. Perhaps the authors are trying to deprecate “straddle” passes (a definition is here) in favor or complete lane changes, but the latter involve even more “encroachment.”

The study does show generally positive results for behavior of both bicyclists and motorists following installation of shared-lane markings. That highlights the importance of correct placement of the markings, an issue which has become significant since their approval. The markings did not reduce filtering forward, but that is hardly to be expected, because filtering forward occurs when a lane is blocked by of stopped traffic.

Site Descriptions

Figure 3 — note that Guadalupe Street is one-way with 4 lanes, and that SLMs have been placed in both the right and the left outside lanes. This is unusual and might affect the results.

E 51st Street is a four-lane arterial that connects the suburban neighborhoods of north-central and north-east Austin. The facility has bicycle lanes west of Airport Boulevard and east of IH-35, but the lane width between Airport Boulevard and IH-35 is narrow, forcing bicyclists and motorists to share the road.

It would be more accurate to say that they share a lane.

Figure 7 — shows rather tight clearance next to a bus passing an SLM 11 feet from the curb, with parking, but no bicyclist is present. The SLM distance from the curb is the minimum specified in the MUTCD. Only small cars are shown parked at the curb.


The same safety criteria are repeated here as in the Executive Summary. Some of the same inaccurate terminology is used as in the BMUFL report (e.g., “incomplete passing maneuver” instead of “straddle pass”. The term “avoidance maneuver” is used incorrectly, as it is in the bike box report as well:

Avoidance maneuver – An avoidance maneuver was recorded whenever a bicyclist rode outside of the lane (e.g. rode on the sidewalk or cut through a driveway to turn).

This is a choice of route, not an avoidance maneuver, which is an emergency maneuver to avoid a collision.

There are other confused definitions:

Incomplete passing event – An incomplete passing event was recorded when the motorist passed a bicyclist without changing lanes.

This is an in-lane pass, not an incomplete pass. An incomplete pass would occur if a motorist initiates a pass and then decides not to pass.

Encroachment – Encroachment was recorded when a passing motorist occupied two lanes while passing.

This is not encroachment. It is a straddle pass, as defined and named accurately by Dan Gutierrez and Brian DeSousa in their report already cited. The motorist must yield to traffic in the lane he/she merges into.


Substantial changes in bicyclist and motorist behavior were recorded on Guadalupe Street and Dean Keeton. Reduction in sidewalk riding was more significant than change in bicyclist lateral position when on the roadway.

Changes were more subtle on E. 51st Street.

I note that the increase in bicyclist filtering forward (“bypassing the queue”) can be explained easily enough in that fewer bicyclists were on the sidewalk, and so more were able to bypass.

Conclusions and Recommendations

I generally agree with the conclusions and recommendations — that is, I think that shared-lane markings are useful — though I am appalled with the sloppiness of the report’s methodology and use of terminology, and I note that greater improvements would require education, not only placement of markings.

Lyon study — cyclists ride faster in rush hour?

A blog posting published by the Massachusetts Institute of Technology describes a study of cycling in Lyon, France.

News accounts of the report are making some rather strange assertions, such as that cyclists ride faster during rush hour than in the middle of the day, and faster on Wednesdays. On the other hand, the Lyon study is very interesting in that it aggregates data on millions of bicycle trips, recorded in the database of Lyon’s card-swipe bicycle-rental system.

I see two problems with this study, and more so with news items about it: not all data were collected that would be needed to describe cyclists’ trips accurately; also, there is a rush to conclusions, without looking at some rather important characteristics of cyclists’ trips.

Certainly, cycling can achieve shorter trip times than motoring when motor traffic is congested, whether by cyclists’ filtering forward on the same street or by choosing other streets, paths, riding against traffic, whatever. What I can’t grasp is how any individual cyclist would achieve a shorter travel time in rush hour than at other times.

Congested motor traffic slows bicyclists, though not as much as it slows motorists — because cyclists have a lower speed capability in the first place, and because cyclists have a greater choice of routes, and can filter forward. Even with bike lanes (of which, according to the article, Lyon doesn’t have any), congested motor traffic slows bicyclists. But also, congested bicycle traffic and pedestrian traffic slow bicyclists.

The Lyon data include only the times and locations of rental and return of the bicycles, and odometer readings. The data, then, cannot show where bicyclists went, and can record only an average speed. Importantly, the slower mid-day times may reflect rentals during which the bicycle is parked in mid-trip — shopping trips, or trips to appointments, lunch dates, classes, (Lyon is a major university city). Women’s speed capability is generally only slightly lower than men’s; to claim it as an important explanation is at least vaguely offensive. Morning and evening bicycle commuters, whether male or female, might be regular bicycle users, in better physical condition, more skillful in traffic and so capable of higher speeds. Without demographic data, there’s no way to know.

The report does include some interesting results about the shortest travel times, which it is safe to assume do not involve parking in mid-trip.

Bicycles included in the study are available at rental stations spaced around Lyon. A renter may obtain a bicycle at one station and leave it at another, making the system practical for single-direction trips. But renters must walk to the stations — the bicycles are, for example, not at their homes. Bicycles will not be used for the shortest trips unless stations happen to be very convenient to trip origins and destinations. Also, the system works only within the limited area where stations exist. These factors can be expected to affect the trip lengths recorded in the study.

I look forward with eager anticipation to a study using GPS data correlated with user data, so it is possible to categorize the cyclists, determine where they went, how fast they actually rode, and whether they parked the bicycle in mid-trip.

Davis, California historical documents

Thanks to John Ciccarelli, Robert Sommer and David Takemoto-Weerts — and David’s students — among others — I am able to post online a number of documents about bicycling in Davis, California and the Davis bicycle program. Davis has the longest experience with a bicycle program of any city in the USA, and a large population of cyclists thanks to its being the home of the University of California at Davis.

You may surf to my table of contents page for the Davis documents and a complete list of people I have to thank — but also please read the rest of this post:

Of particular note are the conclusions which Davis has reached about different types of bicycle facility designs. Davis pioneered some brilliant design innovations, for example, bicycle traffic circles. On that topic, also see videos here and here.

Davis also has been willing to learn from mistakes and move onward. In another post, I have assembled quotes about Davis’s experience with barrier-separated bike lanes, versus conventional bike lanes separated from the adjacent lane only by a painted stripe, an issue which is particularly relevant as I write this in 2010.

I approve of this?

UPDATE: This post gives background information on the intersection. I have now ridden through it, and my opinion of it has changed. I have another post about it, and a video. Please check them out.

The image below shows a special installation of traffic signals and markings at the intersection of 16th street, U Street and New Hampshire Avenue NW in Washington, DC. To enlarge the image so you can read the text descriptions, click on it. You also may have a look at a Google map satellite view. Then please return to this page for my comments.

16th Street, U Street and New Hampshire Avenue NW, Washington, DC

16th Street, U Street and New Hampshire Avenue NW, Washington, DC

Pierre L’Enfant and Andrew Ellicott — and let’s also not forget African-American surveyor Benjamin Banneker — laid out Washington’s streets from scratch —  in the pre-automotive 1790s. Washington’s diagonal avenues give it an openness and unique sense of place — but the resulting uneven-length blocks and multi-way intersections make for some serious headaches now. Some traffic movements are odd, traffic signals can not be synchronized efficiently…

Before the new installation, no signals in this intersection faced new Hampshire Avenue. Bicyclists would sometimes use New Hampshire Avenue for through travel, though its conflicting one-way segments made that illegal and there was no conflict-free crossing interval.

The illustration above is from a page posted by the government of the District of Columbia describing a new installation of contraflow bicycle lanes, bicycle waiting boxes and special traffic signals. At first glance, these may raise the hair on the back of the necks of people who are suspicious of special bicycle facilities treatments.

Look again. The bike boxes look odd only because they connect with diagonal New Hampshire Avenue. They are cross-street bike boxes — which bicyclists enter from the left. Bicyclists from New Hampshire Avenue enter on a separate signal phase from the motor traffic on 16th Street, rather than to creep up on the right side of motor vehicles, as with more-usual bike-box installations. Motorists do not have to crane their necks or stare into a right-side mirror looking for these bicyclists.

The cross-street bike boxes are even more conflict-free than usual. Because only bicycle traffic runs contraflow, bicyclists do not have to negotiate with any right-turning traffic when entering the intersection.

To summarize: this installation, importantly, does not violate the fundamental traffic-engineering principle of destination positioning at intersections, as so many special bicycle facilities installations do.

Or, looking at the same conclusion from a different point of view, the installation does not require or encourage bicyclists to do anything dangerous or stupid, and it offers reasonable travel efficiency considering the situation it addresses.

I am not going to say that this installation is perfect. I can see the following issues.

  • Bicyclists’ having to wait through two traffic-signal phases is inconvenient and might lead to scofflaw behavior. A “scramble phase” could allow crossing in one step and might even apply to bicyclists arriving from other directions. It would reduce the time allocated to for all the other phases, but it might be practical, and preferable, at times of low traffic. Signals and markings which only apply at some times could, however, be confusing.
  • The installation addresses only bicycle traffic entering the intersection from New Hampshire Avenue. Traffic control remains as it was for 16th street and U street. Considering the many ways in which bicycle travel could be made slower and/or more hazardous in the name of making it better, this may be a case of “best leave well enough alone,”  but on the other hand, real improvements might be possible.
  • The bike boxes on 16th street could be interpreted as encouraging bicyclists on that street to overtake motorists on the right, then swerve in front of them, as is the more conventional with bike boxes.
  • Just outside the lower left of the picture on New Hampshire Avenue, there is wrong-way parallel parking next to the bike lane. Motorists exiting wrong-way parking spaces are in head-on conflict with bicyclists, but cannot see them if another vehicle is parked ahead. (See illustrated description of wrong-way parallel parking elsewhere, if the explanation here is unclear.) At the top right, on the other hand, note that the bike lane is farther from the curb: this segment of New Hampshire Avenue has back-in right-angle parking, avoiding the sight-line problem.
  • And, while we’re at it, I have another issue with the street grid, though it’s common to many other cities and not readily subject to correction. Streets that go east and west guarantee that twice per year,  for several days, the Sun will rise and set directly along the streets, glaring into drivers’ eyes.  If the street grid ran northeast to southwest and northwest to southeast, this would never happen. All you Pierre L’Enfants of today designing new cities, please take notice, here’s your chance to acquire a reputation as Pierre L’Enfant Terrible!

This installation is the subject of experimentation sanctioned by the U.S. Federal Highway Administration, with observation, data recording and analysis to see how it works in practice. The experimentation may turn up more issues, or reveal that some are of little importance.

Now, dear readers, you also may also have points to add to the discussion. Let the comments fly.

See also: GreaterGreaterWashington blog entry about this installation; Washington, DC Department of Transportation page about it; Google maps satellite view.

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

The full report is available online:


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!

Bike box rationales

On another Web page, I have discussed the features and operational characteristics of so-called “bike boxes”, in which bicyclists wait for traffic signals ahead of the stop line for motor traffic. I recommend that page as background information for this discussion.

In this posting, I will discuss rationales advanced for the installation of bike boxes.

There are two principal rationales for a bike box, one of which I regard as valid but which might better be served by a different implementation. The other rationale, I find very distressing.

The first rationale is to accommodate a high volume of bicycle traffic, where bicyclists might have to wait through multiple signal cycles behind motor traffic, or else might filter forward and then not have room to wait. I recommend that bicyclists wait behind the first motor vehicle, so as not to be caught on the light change, and to negotiate with the driver of the second vehicle in line. That places the bicyclist in the exhaust of the first vehicle, but that’s better than risking a right hook collision. The exhaust problem has become far less serious in countries which have mandated pollution control on motor vehicles. But — there’s only so much room behind the first vehicle for a couple of bicyclists. A bike box behind the first vehicle would formalize that option, but unfortunately, the length of vehicles varies.

A bike box is advantageous in terms of bicyclists’ travel time when going straight through the intersection, if it facilitates filtering forward past stopped traffic — though, on the other hand, it increases motorists’ travel time. The bike box makes no significant difference in a bicyclist’s through travel time when the bicyclist arrives on the green.

But a bicyclist can get caught at the right side of the roadway when approaching the bike box, and the light turns green. Merging into the flow to go straight, or make a vehicular left-turn, is more advantageous unless traffic is very congested. (And that’s one reason among others that use of a bike lane should not be mandatory!)

The other rationale for a bike box is to encourage more people to ride bicycles by increasing comfort. I find this rationale very scary when the supposedly comfortable facility includes a deathtrap. I call this the “Pied Piper” approach to bicycle planning. It involves some convoluted thinking — bicyclists fear motorists, so, build facilities which appear less scary to the bicyclists.

A bike box with a pre-green signal interval (red and yellow in European practice) provides a warning for a bicyclist not to overtake and swerve in front of the first motor vehicle waiting at the intersection as the light turns green. He/she can still get stuck waiting for through traffic to clear, and the signal to turn red, then green again, if the intention using the bike box was to prepare a left turn (as with a Vancouver, BC bike box and some in New York City) or to cross to the other side of a one-way street (as with a bike box in Eugene, Oregon).

Motorists waiting behind a bike box without the pre-green are expected to look for bicyclists in their right rear-view mirror while also scanning the intersection ahead. That increases the likelihood of mistakes in both tasks, but also, the right rear-view mirror doesn’t provide complete coverage of the area where a bicyclist may be, particularly for the driver of a truck or bus with a high cab and a hood. If the motorist doesn’t look into the mirror at the right time, the bicyclist may have passed outside the field of view seen in the mirror. That is the rationale for additional mirrors, beepers, bicyclist-presence actuated flashers etc. that have been proposed to warn motorists of bicyclists overtaking on the right, and warn bicyclists of motorists preparing to turn right — none of which measures have been implemented in practice and all of which are technological solutions, with the attendant problems of implementation rollout and reliability.

So: what to recommend? here’s what I suggest. Never overtake a long truck or bus with less than 5 feet of clearance to its side, not even in a bike lane. Preferably, overtake on the left or move forward in line with other traffic, but in a traffic jam, you may filter forward *slowly* in a bike lane. Be aware of thehazard of car doors opening from either side, pedestrians stepping out form in front of tall vehicles, etc. Never swerve across in front of a vehicle unless you can be entirely sure that it will not start to move. Make eye contact with the driver, signal your intentions. If you can’t see the driver in a high-cab vehicle, just don’t swerve left. Pulling into line behind a vehicle that is waiting for a traffic signal or stop sign is reasonably safe if you obey these precautions. Swerving across in front of a vehicle waiting first in line, even with a bike box, is only safe if you can be sure that the traffic signal is not about to change.

Alternatives to the bike box?, For less-skillful bicyclists in urban areas, I favor the bicycle boulevard concept, in which bicyclists and motorists share a roadway according to the normal vehicular rules of the road, on a street with low traffic volume — typically, a residential street paralleling an arterial, using diverters and small traffic circles to keep down the volume and speed of motor traffic. This approach avoids the problems with attempting to accommodate conflicting movements with special facilities on a street that also carries heavy motor traffic. There are tradeoffs, to be sure: the bicycle boulevard isn’t a main street, so it may not provide such a direct route between as many trip endpoints — and unless bicycle transportation is taken very seriously, the bicycle boulevard may not have as favorable signalization as a main street. I have seen and ridden bicycle boulevards in Berkeley and Eugene, and they do seem to work rather well in those cities. No, I don’t have use or crash data, only my personal observation.